Heista

Upload an image to a brand by URL. The pipeline downloads it, runs the vision tagger (classifies type, detects product name, flags is_primary_product), stores it in the brand-assets bucket, and inserts a brand_assets row. Paid (vision tag credit). If vision tagging fails, the asset is still saved with type=general and can be retried via retag_brand_asset.

Browse proven ad formula blueprints — structural patterns clustered from 3-10+ winning ads that independently converged on the same beat architecture while Meta kept rewarding them with sustained spend. Takes optional filters: vertical, creative_format (e.g. TALKING_HEAD, UGC, FOUNDER_STORY), marketing_angle, algo_intent, hook_type, and limit (1-10, default 5). Each formula returns: source ad count, average active days (runtime proof), confidence score, 6-layer beat blueprint, per-beat visual direction, marketing angle, psychology mission. Free, read-only, idempotent. Use this when the user asks "what's working in [category]", "show me formulas for talking-head ads", "what scripts work in my vertical", or wants category-level pattern discovery before committing to a single ad. Pass the returned formula id to generate_adscript with source_type="formula" for synthesis. When choosing among results: prioritise (1) avg_active_days as primary proof, (2) marketing_angle alignment with the brand's buyer tension, (3) source_ad_count for cluster robustness, (4) confidence_score as tiebreaker. Do NOT use when the user names a specific ad — decode that ad with decode_ad. Do NOT use for sentence-level transcript fidelity — formulas abstract the structure, not exact copy.

Invoke a Creative Agent (character) preset. Every preset is a purpose-built character the workspace has authored or the Heista catalog has published — copy voice, art direction, strategy, creative direction, etc. ONE-SHOT: give the character a message, get its response back as text. Discover callable presets via list_creative_agent_presets. Workspace-authored presets are only callable inside their owning org; official templates (visibility=public_template) are callable from any authenticated org. INPUTS: agent_id (UUID from list_creative_agent_presets), message (the turn text), optional brand_id (server-loads multi-strategy brand summary for character context), optional working_context (light labels the character reads as IN SCOPE — pinned brand + strategies + documents + playbook), optional thread_id (continuity id), optional idempotency_key (5-minute retry safety). Returns the character's response as plain text plus a structured envelope with usage, model, provider, thread_id. Metered — cost depends on character model + context size, typically 2-10 credits per turn. Charged after success on real token usage.

Heista's creative direction engine — same engine the Creative Director specialist runs internally, exposed over MCP. ONE-SHOT: give a brief, get N finished creative outputs. For back-and-forth refinement, or output shapes the `medium` enum below does not cover, use chat_with_creative_worlds instead. OUTPUT SHAPE switches on the `medium` arg: • omitted → N territory cards (default exploration). Each card sits on different psychology / craft / feel / world axis coordinates so the set spans the creative space rather than orbiting one insight. Card has: name, campaign line, 5-8 sentence pitch, one-sentence strategic bet, resolved axis state names, creative-director rationale. • `tvc` → N TVC scripts (15-90s — hook, arc, resolve, sound design, end line). • `billboard` / `ooh` / `print` → N out-of-home concepts (visual concept + line + placement rationale). • `social` → N social-video concepts (hook + format type + middle beat + payoff, optimised for Reels / TikTok / Shorts). • `activation` / `experiential` → N activation concepts (space design + user journey + peak moment + takeaway artifact). • `audio` → N sonic / radio concepts (sonic scene + voice + audio arc). • `campaign` → N full campaign platforms (insight → big idea → strategy → visual world → production roadmap). The engine can also produce manifesto / copy, naming, packaging, PR stunts, content series, brand positioning, partnerships — these output shapes are NOT in the medium enum, so use chat_with_creative_worlds when the user wants one of those. USE WHEN: user says "give me ideas / options / directions / territories", "what angles work for...", "show me three / five ways to...", "write a TVC for...", "draft billboard concepts for...", "I need fresh thinking on...". DO NOT USE to refine one existing direction (use chat tool), to critique work, for OKRs / internal docs / strategy decks, or anything outside advertising creative direction. INPUTS: brief (the creative problem, free text), count (2-6 concept…

Multi-turn conversation with Heista's creative direction engine — a real chat where the agent decides each turn what to produce based on what you ask for. Use whenever the work needs more than one round, OR when you want an output shape not covered by call_creative_worlds' `medium` enum. WHAT YOU CAN ASK FOR (any of these, turn 1 or any turn after): • Territories — "give me five directions for X", "what angles work here" • A TVC script — "write a 30-second TVC for Cowboys" • Billboard concepts — "three billboards under a quiet-authority lens" • A campaign platform — "build #2 into a full campaign with the big idea" • A manifesto or copy — "draft the manifesto in the brand voice" • Naming — "name this product, five options with rationale" • A PR stunt — "what's the newsworthy version of this" • A content series — "20 episode ideas for a brand podcast" • Packaging, sonic branding, partnerships, social systems • Refinement — "make #2 darker", "extend that into a tagline", "summarise" • Pivots — "forget the soft-drink angle, try the late-night insomnia one" SESSION: omit session_id on turn 1; the response returns a fresh session_id you pass on every subsequent turn — that is how the conversation persists. brand_id is only honoured on turn 1 of a new session (continuing sessions keep their original brand context). USE WHEN: user wants back-and-forth, OR wants an output shape outside the medium enum (manifesto, naming, press release, content series, packaging, etc.). Prefer call_creative_worlds when the user wants "three options, done" with no follow-up. WON'T DO: write OKRs / internal docs / strategy decks; behave as a general assistant. It is a creative director with creative-director taste — anti-cliché, specificity test, will push back on vague briefs. Metered — typically 2-10 credits per turn depending on tool use and context size. Charged after each turn on actual token usage.

Check the calling user's Heista API credit balance, month-to-date usage broken down by operation, lifetime spend, and the current pricing for every paid tool. Takes no inputs. Returns balance in cents, lifetime spend in cents, month-to-date call counts per tool (decode_ad, create_powersource_*, generate_adscript), per-tool unit pricing, and a top-up link the user can follow to add credits. Free, read-only, idempotent. Use this whenever the user asks about credits, balance, usage, how much they've spent, top-ups, pricing, "what does this cost", or "how many credits do I have". This is also the ONLY surface where dollar amounts are legitimate to report in conversation — everywhere else, cost should be referenced in credits, not currency. Do NOT use to add credits or change billing — only to read state. Do NOT call this on every turn — invoke once when the user explicitly asks about account state.

Build a complete creative intelligence profile from internal brand documents — creative briefs, brand guidelines, product specs, customer research, competitive analysis. Takes any mix of file_ids (from a previous upload), document_urls (public PDF/DOCX/TXT/MD links, up to 10), or documents_inline (base64-encoded files with filename), plus an optional context_url for layering live brand context (colors, fonts, current messaging) and optional idempotency_key. Returns a job_id; poll with get_powersource. Output shape is identical to create_powersource_url: identity, offer, selling points, voice, buyer profile, tensions, angles, emotional arcs, ctas, narrative. Use this when the user says "I have a brief", "here's my brand guidelines", "use this document", drops a PDF / DOCX / strategy deck, or when the truth lives in internal materials rather than the public website. The pipeline reads text only — convert PDFs to markdown before submitting via documents_inline when possible. Costs 100 credits. Do NOT use for URL-only scans — use create_powersource_url. For URL + docs combined (highest fidelity, triangulates public messaging against internal strategy), use create_powersource_full.

Build the highest-fidelity creative intelligence profile by combining a brand's public website URL with their internal documents. Takes a required website URL plus at least one document — file_ids from previous upload, public document_urls (PDF/DOCX/TXT/MD, up to 10), or documents_inline (base64-encoded). Optional idempotency_key for safe retry. Returns a job_id; poll with get_powersource. Same response shape as create_powersource_url, but the synthesis cross-checks how the brand presents publicly against what the team actually believes internally, producing stronger conviction on voice, positioning, proof, and tension architecture than either input alone. Use this when the user has both a public site AND a brief / brand guidelines / strategy deck and wants the deepest possible profile — the kind of intelligence a senior strategist produces over a week. Default recommendation when both inputs are available. Costs 200 credits. Do NOT use for URL-only scans — use create_powersource_url (100 credits). Do NOT use for docs-only scans — use create_powersource_docs (100 credits).

Build a complete creative intelligence profile of a brand from a single website URL. Takes a website URL (homepage, PDP, landing page) plus optional idempotency_key, force_refresh, and webhook_url. Returns a job_id immediately; poll with get_powersource every 3-5s (typically 60-90s total). The final payload contains 14 structured sections: identity, offer, selling_points, brand_story, brand_style, brand_assets, brand_voice, buyer_profile, 12 buyer tensions, marketing angles, emotional_arcs, ctas, proof_assets, and strategic narrative. Use this when the user says "analyse my brand", "load my brand", "build a strategy from my site", "what should my ads say", "decode this website", or pastes a homepage / competitor URL and wants a brand profile (not an ad decode). Also use this as the brand layer before calling generate_adscript — pass the returned powersource_id. Costs 100 credits. Re-scanning the same URL within your org returns the cached result free. Do NOT use for internal docs / PDFs / brand guidelines — use create_powersource_docs. For URL + docs combined (highest fidelity), use create_powersource_full. Do NOT use to decode a video ad — use decode_ad.

Permanently delete a Creative Library draft that has NEVER been published. Refused for any article with publication history — use creative_unpublish_article to take a live page down instead, which keeps the draft. Use this only to clear test or abandoned drafts.

Read the canonical shelves, taxonomy, relationship Lego, safe content rules, and positional slots for every publishable Creative Library format. Call this before authoring.

Read one Creative Library draft so it can be reviewed before explicit publication.

Read one shelf hub as an object: its public URL, what it covers, what it deliberately does NOT cover (and which shelf owns each of those instead), and every article on it with status and live URL. Use it to check placement before drafting.

List Creative Library drafts and publication state. Returns editorial metadata only, not customer data.

Publish only the exact reviewed draft revision. If the draft changed after review, publication fails and the new revision must be reviewed.

Validate and save a complete Creative Library draft using the canonical taxonomy and format-specific content slots. An identical retry is a no-op. It cannot replace published content or publish a page.

Take a live Creative Library article down. It stops being public and leaves the sitemap immediately. The draft is preserved and can be re-published after review. Use this to reverse a publication.

Change an article slug and 301 the old URL at the new one. Never leaves two live URLs. Refuses a new slug ending in a year, a slug already in use, and any article whose draft is ahead of what is published (renaming republishes). Use this instead of saving a second article under a new slug.

Decode a specific video ad URL into its full structural formula — beat-by-beat breakdown, hook classification, behavioral psychology stack, creative format, runtime performance signals (active days on Meta Ad Library when available), and per-cut visual data. Takes one video URL plus an optional idempotency_key. Returns a job_id immediately; poll with get_decode every 15s until status is "completed" (typically 45-60s end-to-end). Use this when the user pastes an ad URL, names a specific competitor ad, asks "decode this" or "break down this ad" or "what makes this ad work", or wants sentence-level fidelity to one specific winner before writing a script with generate_adscript. Supports Facebook Ad Library, TikTok, Instagram Reels, YouTube Shorts, and direct .mp4 URLs. Costs 15 credits for videos ≤60s, 20 credits for 61-120s. Do NOT use to browse the corpus or find ads by category — use decoder_intelligence or adformula_intelligence (both free) for discovery. Do NOT use for image ads or static creative.

Browse individual decoded ads from Heista's corpus of real winning Meta/TikTok creative. Takes optional filters: vertical, creative_format, marketing_angle, hook_type, algo_intent, brand (partial name match), and limit (1-10, default 5). Each result returns beat timeline, classification, psychology, runtime performance signals (active days on Meta when available), and a decode id you can pass into generate_adscript with source_type="decode" to write a fresh script on that exact structure. Free, read-only, idempotent — no credits consumed. Use this when the user wants a specific ad as a script template (not an averaged formula), asks "show me winning ads in [vertical]", "what are [brand]'s top ads", or wants to see examples before committing to a generation. Source discovery surface — the response is the spine; for the full bundle with transcripts and director's read, call get_decode by id afterwards. Do NOT use to decode a NEW ad from a URL — use decode_ad (paid). Do NOT use for category-level patterns abstracted across multiple ads — use adformula_intelligence. Do NOT use to write the script itself — use generate_adscript or write directly from the bundle.

Delete one brand asset by asset_id. Removes the brand_assets row and (when the asset was uploaded rather than scanned) the storage object. Destructive — confirm with the user before calling. Use list_brand_assets first to find the asset_id.

Delete one saved asset by id. Destructive — confirm with the user before calling. OAuth callers can only delete saves they created themselves (Linear model — see /assets UI for org-admin override). API-key callers are treated as org-trusted and can delete on behalf of any creator in the workspace. Cleans up the storage object for private VISUALS/MOTION saves.

Dispatch to the DESK RESEARCHER — source-grounded synthesis on a topic landscape. Use for: "what is known about X / give me the landscape of Y / fact-check Z / synthesize the published evidence on W". Multi-source FACT/INFERENCE extraction with citation discipline. Vertical and geography agnostic. Returns: BRIEF restatement + NOT IN SCOPE + findings with FACT/INFERENCE/SPECULATION labels + [n] citations + Sources block. NOT for: trajectory questions (use dispatch_trend_researcher) / entity teardowns (use dispatch_market_analyst) / numerical effect sizes (use dispatch_quantitative_researcher) / community quotes (use dispatch_qualitative_researcher).

Dispatch to the DESK RESEARCHER — source-grounded synthesis on a topic landscape. Use for: "what is known about X / give me the landscape of Y / fact-check Z / synthesize the published evidence on W". Multi-source FACT/INFERENCE extraction with citation discipline. Vertical and geography agnostic. Returns: BRIEF restatement + NOT IN SCOPE + findings with FACT/INFERENCE/SPECULATION labels + [n] citations + Sources block. NOT for: trajectory questions (use dispatch_trend_researcher) / entity teardowns (use dispatch_market_analyst) / numerical effect sizes (use dispatch_quantitative_researcher) / community quotes (use dispatch_qualitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Run a full research workflow via the Head of Research agent. The Head decomposes your brief into specialist sub-questions, dispatches the right combination of 6 specialists (desk, trend, market, quant, qual, social) in parallel via async dispatch, polls them to completion, judges output quality, and returns a structured synthesis. Use for: any source-grounded research request — fact-checking, vendor teardowns, trend assessment, quantitative effect-size analysis, qualitative theme extraction, cross-platform discourse mapping, or any combination. Wall time: 2-5 min typical. Returns: { synthesis, head_session_id, status, event_count, tool_uses, elapsed_ms }. NOT for: non-research requests (writing, coding, casual chat) — respond directly without calling this. Cost: $0.20-1.50 per call depending on brief complexity (specialist token spend + Anthropic session-runtime at $0.08/hr).

Dispatch to the MARKET ANALYST — entity-deep teardown of a named brand or vendor. Use for: "what is brand X / how does company Y work / decode competitor Z / teardown vendor W". Multi-axis extraction grounded in multi-class sourcing, plus defensible MOAT and credible GAP theses. Vertical and geography agnostic. Returns: 8-axis extraction (positioning / offer / audience / voice / pricing / distribution / proof / trajectory) + MOAT thesis + GAP thesis + Sources. NOT for: topic landscapes without a named entity (use dispatch_desk_researcher) / trajectory questions about a category (use dispatch_trend_researcher).

Dispatch to the MARKET ANALYST — entity-deep teardown of a named brand or vendor. Use for: "what is brand X / how does company Y work / decode competitor Z / teardown vendor W". Multi-axis extraction grounded in multi-class sourcing, plus defensible MOAT and credible GAP theses. Vertical and geography agnostic. Returns: 8-axis extraction (positioning / offer / audience / voice / pricing / distribution / proof / trajectory) + MOAT thesis + GAP thesis + Sources. NOT for: topic landscapes without a named entity (use dispatch_desk_researcher) / trajectory questions about a category (use dispatch_trend_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Dispatch to the QUALITATIVE RESEARCHER — thematic synthesis from unstructured text (interviews, reviews, forum threads, customer language). Use for: "what are the 2-3 recurring themes in how D2C founders talk about X / what language is being used around Y / what are the patterns in customer reviews of Z". Every theme carries evidence count, triangulation status, ≥1 verbatim quote, outlier-check note. SOLVES the Reddit/X/Substack named-operator voice retrieval gap that legacy search tools could not fill. Returns: Corpus + Sampling + Coding methodology + 4-axis Themes table + Theme synthesis + Outlier voices + Saturation assessment + Sources. NOT for: quantitative effect sizes (use dispatch_quantitative_researcher) / multi-platform discourse mapping (use dispatch_social_listening_researcher).

Dispatch to the QUALITATIVE RESEARCHER — thematic synthesis from unstructured text (interviews, reviews, forum threads, customer language). Use for: "what are the 2-3 recurring themes in how D2C founders talk about X / what language is being used around Y / what are the patterns in customer reviews of Z". Every theme carries evidence count, triangulation status, ≥1 verbatim quote, outlier-check note. SOLVES the Reddit/X/Substack named-operator voice retrieval gap that legacy search tools could not fill. Returns: Corpus + Sampling + Coding methodology + 4-axis Themes table + Theme synthesis + Outlier voices + Saturation assessment + Sources. NOT for: quantitative effect sizes (use dispatch_quantitative_researcher) / multi-platform discourse mapping (use dispatch_social_listening_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Dispatch to the QUANTITATIVE RESEARCHER — numerical analysis with full methodology context. Use for: briefs that turn on numbers done rigorously — "what is the documented effect size of X / what does the data say about Y / quantify the impact of Z". Every load-bearing number carries sample frame, sample size, measurement instrument, time window. Often answers with insufficient-evidence when underlying data is thin (negative findings are deliverable). Returns: 4-axis Quantitative summary (Value / Methodology rigor / Effect size / Robustness) + Numerical findings table + Methodology gaps + Sources. NOT for: topic landscapes (use dispatch_desk_researcher) / community language patterns (use dispatch_qualitative_researcher).

Dispatch to the QUANTITATIVE RESEARCHER — numerical analysis with full methodology context. Use for: briefs that turn on numbers done rigorously — "what is the documented effect size of X / what does the data say about Y / quantify the impact of Z". Every load-bearing number carries sample frame, sample size, measurement instrument, time window. Often answers with insufficient-evidence when underlying data is thin (negative findings are deliverable). Returns: 4-axis Quantitative summary (Value / Methodology rigor / Effect size / Robustness) + Numerical findings table + Methodology gaps + Sources. NOT for: topic landscapes (use dispatch_desk_researcher) / community language patterns (use dispatch_qualitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher).

Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Dispatch to the TREND RESEARCHER — recency-dominant trajectory investigation. Use for: "is X a real trend / what is happening with X right now / where is X headed / what is driving X". Distinguishes trend from spike, signal from noise, real shift from echo chamber. Commits to falsifying conditions before searching. Returns: 4-axis Trend assessment (Reality / Magnitude / Direction / Horizon) + Current state + Baseline + trajectory + Drivers + Counter-signals + Sources. NOT for: static landscape questions (use dispatch_desk_researcher) / entity teardowns (use dispatch_market_analyst) / numerical analysis (use dispatch_quantitative_researcher).

Dispatch to the TREND RESEARCHER — recency-dominant trajectory investigation. Use for: "is X a real trend / what is happening with X right now / where is X headed / what is driving X". Distinguishes trend from spike, signal from noise, real shift from echo chamber. Commits to falsifying conditions before searching. Returns: 4-axis Trend assessment (Reality / Magnitude / Direction / Horizon) + Current state + Baseline + trajectory + Drivers + Counter-signals + Sources. NOT for: static landscape questions (use dispatch_desk_researcher) / entity teardowns (use dispatch_market_analyst) / numerical analysis (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

Toggle the favorite flag on a saved asset. Pass is_favorite=true to favorite, false to unfavorite. favorited_at is set/cleared in lockstep so the Favorites tab sorts correctly. Not destructive.

Drill into a specific URL after search surfaces it. Returns the extracted text content plus metadata. Internal routing: PDFs hit Anthropic Files API for OCR + structured extraction; HTML pages are fetched + text-extracted via readability-style stripping. Use for: verifying a verbatim quote from a Reddit thread, reading a primary source in full (earnings transcript, research paper), drilling into a vendor product page after search surfaced the URL. NOT for: discovering new URLs — use search/search_community/search_research first. This tool takes a known URL only. Optional max_chars 100-50000, default 8000. SSRF-protected: private IPs + localhost blocked.

Aggregate marketing analytics for the last 7/28/90 days: pageviews, visitors, sessions, AI-search-referred sessions, the view→engaged→CTA→signup→trial funnel, and top pages. Aggregates only — never person-level data. FUNNEL EVENTS, so you know what each step counts: views = $pageview; engaged = pseo_session_summary with properties.engaged (scroll ≥25% or dwell); CTA = pseo_session_summary with properties.cta_clicks_count > 0, where a CTA is a click on a link to /auth/signup, /auth/login, /book-demo, /pricing or /workspace, or any element marked data-cta; signup = signup_completed; trial = trial.started. CTA auto-detection and Creative Library session tracking both began 2026-08-24 — a CTA step that rises from ~0 across that date is instrumentation landing, not a conversion change, and library figures before it were never measured. Any step that exceeds its 25s deadline reports TIMED OUT and is NOT a zero. Returns an error result if product analytics is not configured. Read-only.

Top marketing pages by views for the last 7/28/90 days, optionally filtered to a path prefix (e.g. "/decode", "/intelligence", "/brands"). Includes engagement signals where captured. Aggregates only, hard cap 50 rows. Read-only.

Daily pageview series for the last 7/28/90 days, split by traffic source category (ai_search / organic / social / direct / referral). Use to measure launch weeks and content momentum. Aggregates only. Read-only.

Server-logged crawler fetches: which AI engines (GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, …) and search crawlers (Googlebot, Bingbot) fetched which heista.co pages, and when. This signal is invisible to page analytics — crawlers never run the tracking script. Group by bot, page, or date; filter by bot or path. Logging began 2026-07-23 (no earlier history exists). 180-day retention. Read-only.

File an issue on the Heista HEI board: title, markdown description, optional labels (Bug, Feature, Improvement, Security, SEO, Tech Debt, Upstream, In-App Support, In-App Feedback) and priority (0 none - 4 low, default 3). Unknown label names are dropped with a warning rather than failing the write. Locked to team HEI. Use it to record a real defect or a piece of work, not to take notes.

Read one live brand report in full by slug, including the creative intelligence payload used on the public brand page — proof points for outreach and positioning. Read-only.

Read one published decode in full by id or slug, including its public structural payload (beats, classification, patterns — the same data rendered on the public decode page). Use for proof points, content briefs, and pattern citations. Not for customer workspace decodes — only the published corpus. Read-only.

Read one Heista Linear issue in full by identifier (e.g. "HEI-14") or UUID: title, state, priority, assignee, labels, full description, and recent comments (including the automated scope/fix notes agents leave). Locked to team HEI. Read-only.

Google URL Inspection for one heista.co URL: index verdict, coverage state ("Submitted and indexed" / "Crawled - currently not indexed" / "URL is unknown to Google"), last crawl time, robots state, and canonical resolution. THE tool for diagnosing why a page has no impressions. Quota ~2,000 inspections/day — batch thoughtfully. Read-only (requesting indexing is not possible via API).

LIVE Google Search Analytics query — group by any dimensions (date, page, query, country, device, searchAppearance; up to 3) with page/query filters over up to 16 months of history. Richer than the snapshot tools: use this for ad-hoc analysis. NOTE: including the "query" dimension omits anonymized rare queries — use ["date"] or ["page"] for complete totals on low-traffic sites. Hard cap 100 rows. Read-only.

Sitemaps registered on the Search Console property with submitted vs indexed counts, last-download time, warnings and errors. The indexing-progress scoreboard — as of Jul 2026 the main sitemap had 2,432 submitted / 0 indexed. Track this as SEO fixes land. No parameters. Read-only.

Google Search performance totals from first-party Search Console data (synced 6-hourly): clicks, impressions, CTR, impression-weighted average position, distinct queries and pages. Optional page-path filter. Data lags real traffic by ~2-3 days; max window 28 days. Read-only.

Top pages by Google search clicks or impressions from first-party Search Console data, optionally filtered to queries containing a term. Use to find which pSEO pages earn search demand. Hard cap 50 rows, max window 28 days. Read-only.