ZeroWidth Prism

Posts a comment on a workspace entity — a new thread, or a reply when rootId is given. Use it to leave findings where the discussion already lives (an eval result on the flow being debated, a summary on a long thread). Mention people via mentionedUserIds (from workspace member ids) to ring their notification bell; never mention someone who didn't ask to be pulled in.

Lists the comment threads on one workspace entity (open first, then resolved) with authors and timestamps. Read this before weighing in on contested work — the threads are where disagreement lives before it becomes a decision.

Sets a comment thread's resolved state (rootId = the thread's root comment id). Resolve ONLY when the human asked or the thread's question is demonstrably settled — and say what settled it in a reply first. Reopening is for new evidence.

Without a tag: every tag in use across the workspace with how many entities carry it, most-used first — the vocabulary the team already organizes by. With a tag: everything filed under it across every tool, each with its kind, id, title, and path. Use it to reuse existing labels instead of inventing near-duplicates, and to answer 'show me everything about X' when X is a label.

Returns the tags on a batch of entities of one kind — the labels galleries organize by. Ids come from the kind's list/get tool or from search_workspace. Use it before entity_tags_set so you replace the full set knowingly, and to answer 'what is this filed under'. Entities the user can't see are omitted.

Replaces the FULL tag set on one entity (an empty list clears it). Read the current tags with entity_tags_get first and pass the merged list — this is not additive. Tags are lowercase letters, numbers, spaces, and hyphens; prefer labels already in use (entity_tags_browse) so the workspace's vocabulary stays small. The id comes from the kind's list/get tool or search_workspace.

Fetch the full Markdown body of a specific docs page by its slug. Use this after `search_docs` when the user needs the complete content of a page. No authentication required.

Enumerate all available docs pages, optionally filtered by product (e.g. 'compass', 'legal', 'overview'). Use this to discover what slugs exist before calling `get_doc`. No authentication required.

Creates a field from an origin idea — the seed of an exploration canvas. Counts against the workspace's field quota. May return `needs_confirmation` — tell the user what you're proposing and wait for approval.

Removes a field and its whole canvas (soft delete; frees the workspace's field quota). Use when the user is done with an exploration or one was created by mistake — studies attached to its nodes are not deleted. Field ids come from prism_fields_list. May return `needs_confirmation` — name the field and wait.

One field's full tree: every node (id, parent, axis, description, pinned, color, whether it has an image / desk research) plus the AI-clustered groups. The origin node has parentId=null; children sit along named axes. Use node ids with the expand / research / study tools.

Lists Prism fields (idea-exploration canvases) in the active workspace: name, origin idea, node count. Fetch one with `prism_fields_get` for its nodes.

Edits a field's name (null reverts to the origin idea), description, or visibility. Nodes are untouched. Field ids come from prism_fields_list. May return `needs_confirmation`.

Promotes an analysis theme (or, with no themeId, the analysis summary) into the workspace's Ledger as a belief, carrying the supporting verbatims as evidence with links back to the study. THE step that turns a finding into workspace memory — use when the user says an insight matters. May return `needs_confirmation`.

Creates a one-on-one AI-led interview on a study and returns the invite link to forward — the guest needs no account. The transcript stays on the study and joins the next analysis run (it never lands in Compass). focusPrompt briefs the interviewer on what to dig into; omitted, it explores the study's territory. May return `needs_confirmation`.

The study's one-on-one qual conversations: guest, status, focus, and — once completed — the structured memo (summary, key claims, tensions, verbatim quotes). Raw transcript included only while no memo exists. inviteUrl is the link to forward for interviews still waiting on their guest.

THE core Prism gesture: generate variations of a node along a named semantic axis ('more visceral', 'for the skeptic', 'stripped to essentials'…) in one of four directions. Runs generation against the workspace's inference credit. May return `needs_confirmation`.

Web-sourced secondary research on a node's idea — market context with citations, stored on the node. depth 'thorough' runs three angled passes (market, evidence, shifts) at ~3× the credit. `focus` steers what it goes after; without one it answers a generic brief off the node's own description, so pass it whenever the user has said what they actually want to know. Runs against the workspace's inference credit. May return `needs_confirmation`.

Sets pinned state and/or the color tag on a node. Pins are the cross-field shortlist. May return `needs_confirmation`.

Stops a queued, running or paused panel run. Answers already in stay. May return `needs_confirmation`.

What running a study against a panel would cost: people, model calls, and approximate dollars of workspace credit. Starts nothing. Tell the person the cost before calling prism_panels_run.

Status, progress, spend and the run's own analysis. For the numbers, call prism_studies_results with panelRunId. Synthetic answers are never people's: always say so when you report them.

Saves a panel from a spec (usually from prism_panels_draft) and draws its people from population records in the background, which takes a few seconds. Visible to the workspace unless visibility is PRIVATE. May return `needs_confirmation`.

Turns a plain description of an audience ("100 Midwest senior citizens") into a panel spec: filters on Census and General Social Survey fields, a size, and stated shares for traits with no data behind them (assumed). Saves nothing. Show the person the spec and assumedNotes, then pass the spec to prism_panels_create. poolSize is how many people in the population sample match.

One panel with its current version and the share of people by every field (assumed fields flagged). Use it to confirm a draw looks like the audience the person meant.

Every synthetic panel the person can see: name, current version (people, status), runs so far, and fit (how far it sat from people the last time a study had both). Reuse an existing panel before drafting a new one.

Starts a background run: every person on the panel answers the study (or, for kind interview, sits with the study's interviewer). Spends workspace credit — give the person the estimate from prism_panel_runs_estimate first. Works on draft studies. Answers land as their own result set, labeled synthetic, never counted as responses. Follow with prism_panel_runs_get. May return `needs_confirmation`.

A cross-study digest: every study with responses — title, origin (standalone / canvas node / tracker wave), response count, latest analysis summary, top themes, and which insights were kept in Ledger. The starting point for 'what have we learned about X?' — follow up with prism_studies_get (insights) or prism_studies_results on the studies that matter.

One desk-research report in full: the brief (markdown) and the sources it cites. Its claims are what public sources say, not what anyone at the company told you; when you put them on the Compass map, cite sourceKind 'prism_report' with this report's id.

Every desk-research report on a study, newest first: id, title, the focus it was asked, depth, status (running / ready / failed) and an excerpt. Read one in full with prism_research_reports_get.

Web-sourced desk research kept as a report on a study, with citations. Steer it with `focus`: research accumulates, a broad sweep first, then narrower runs as the questions sharpen. depth 'thorough' runs three angled passes at ~3× the credit. To research a company, make a standalone study about it (prism_studies_draft_standalone) and run one report per area of the business, e.g. focus 'how finance closes the month and approves spend at <company>, from job posts, filings and press'. It plans questions, searches, reads the pages and keeps only findings it can quote from them, so it takes a few minutes: this returns at once with the report running. Tell the person it's under way, and read it with prism_research_reports_get once its status is ready. Runs against the workspace's inference credit. May return `needs_confirmation`.

Creates a research program that fields the SAME instrument on a schedule — brand tracking, a weekly pulse — each wave an ordinary study. The questions freeze once the first wave fields (that's the trendline), so get them right with the user first. Optionally bind a Ledger metric + score rule so every wave posts a reading (a `scorer` needs a `metricId`). Waves launch on schedule, or on demand with prism_series_launch_wave. May return `needs_confirmation`.

CLOSES the current wave (no more responses; it scores and posts to Ledger if bound) and fields the next one from the series' frozen instrument, readying its participant link. Fielding spends credit for follow-ups, closing chats, and analysis, and closing a live wave can't be undone — say both plainly before proposing. Manual launches don't move the schedule clock. May return `needs_confirmation`.

Recurring research programs (ADR 0031): name, cadence, enabled state, next wave time, wave count, and the metric + score rule when the series posts readings. Waves themselves are ordinary studies.

Edits a series: `enabled: false` pauses the schedule (true resumes), interval / scheduleTime / scheduleTimezone / dayOfWeek move the cadence, name and follow-up / auto-analyze settings change any time. The instrument (questions, scorer) is editable only while no wave has fielded — after that the server refuses with `invalid`, and the answer is a new series. Series ids come from prism_series_list. May return `needs_confirmation`.

Kicks the theme analysis (incremental — reads only responses and interviews since the last run; the previous themes carry forward). Returns immediately with the run's phase; the run continues server-side, so wait a moment and re-read prism_studies_get — findings are fresh once its insights stop reporting an active run. upToDate: true means there was nothing new (a healthy no-op, not an error). Runs against inference credit. May return `needs_confirmation`.

Server-computed banner cut with significance: a target question (scale/number → group means + NPS on 0–10; choice/multi → per-option shares) split by acquisition source or by any single-choice question, each group tested against its complement at 95% (Welch t / two-proportion z). vsRest says higher/lower/not_significant — or not_tested when either side is under the 30-response floor; never present not_tested as 'no difference'. Use this for every 'does X differ by Y?' question instead of eyeballing raw rows.

Permanently deletes a study with its responses, interviews, analysis, and share links. Right for a draft that won't be fielded or a duplicate; for a live study the user just wants to stop, prefer prism_studies_update closed: true — that keeps the data. Study ids come from prism_studies_list_workspace. May return `needs_confirmation` — name the study and its response count, then wait.

Generates a short study (5-8 questions probing the node's problem space — respondents never see the idea itself) and creates it as a DRAFT. The user reviews, previews, and opens it for responses from the study page (or via prism_studies_update publish). Runs generation against inference credit. May return `needs_confirmation`.

Qual-first design: drafts a survey GROUNDED in the study's completed interviews — the recurring claims become measurable questions, the tensions become the choices, in the interviewees' own words. Replaces the study's current questions with the draft (nothing fields until publish). Needs at least one completed interview (see prism_interviews_list). An optional steer biases the instrument ('focus on pricing'). Runs generation against inference credit. May return `needs_confirmation`.

Generates and creates a DRAFT study that isn't tied to any canvas node — brand tracking, workspace-level research, anything you can describe in a sentence. It appears on Prism's Studies page; the user previews and opens it for responses there (or via prism_studies_update publish). Runs generation against inference credit. May return `needs_confirmation`.

One study's questions, response count, open/closed state, and the STORED analysis (summary + themes with strength; insights.activeRun set = an analysis is running right now — wait for it before citing). participantUrl is the live share link to forward when the study is open and one has been minted. Cite theme strengths when reporting results.

Feedback studies attached to one Prism node: title, question count, response count, open/closed.

All studies regardless of origin — standalone, canvas-node, and series waves — newest first: title, question count, response count, draft / live / closed state, and the field / node / series it hangs off. The starting point for 'which studies do we have?'; prism_studies_list is the per-node view, prism_research_digest the findings view. Read one with prism_studies_get.

An AI research analyst writes the report's narrative layer — executive summary, key findings with their numbers, recommendations — from the study's computed record (funnel, per-question aggregates, themes, quotes). Stored on the study; the printable report at the study page renders it above the charts. Runs against inference credit. May return `needs_confirmation`.

Everything the Results tab shows, as numbers you can trust without counting raw rows: fielding funnel (opens → starts → completes, median completion time, sources, per-question drop-off), per-question aggregates (scale distributions + means + NPS on 0–10, choice/multi counts, rank first-place + mean ranks, MaxDiff set scores, word frequencies, text samples), and quality flags (speeders, duplicate participant ids). ALWAYS use this for quantitative questions about a study — never tally answers yourself.

The stored k-means segmentation over the study's numeric answers: named segments with size, share, and the distinguishing features (segment mean vs overall). Null when none computed yet — prism_studies_segments_compute discovers them (needs 30+ responses and 2+ numeric questions).

Runs k-means over the study's numeric answers (silhouette-picked k) and names the discovered segments from their computed profiles. Needs 30+ responses and 2+ numeric questions; recompute overwrites. Runs naming against inference credit. May return `needs_confirmation`.

publish: true takes a draft live (one-way — the participant link starts working). closed toggles whether a live study accepts responses. Also edits the study: title, the `questions` instrument (whole replacement — read prism_studies_get first; LOCKED once responses exist, the server refuses with `invalid` and the answer is a new study), `adaptiveFollowUps` (AI probes on curious answers), the closing chat (`endChatEnabled` + `endChatFocus`), `completionRedirectUrl` for a BYO panel (null clears), and `autoAnalyzeTarget` (null = manual only). Study ids come from prism_studies_list_workspace. May return `needs_confirmation`.

Cross-instrument findings for one subject (today: a Prism node) — attached feedback studies with response counts + theme counts, and whether desk research exists. (Interviews are study-level now — read them per study with prism_interviews_list.) THE PLACE TO LOOK before proposing new research: cite what already exists.