# io.github.derekchoyai/hone (mcpb · hone.mcpb)

Score your judgment over AI-assisted work. Hone scores you, not the model.

- Trust score: 36/100 (low)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- mcpb · `hone.mcpb`: 36/100 (this document), [markdown](https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb.md), [page](https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb)

## Channel facts

- Registry: `mcpb`
- Package: `https://github.com/derekchoyai/hone/releases/download/v0.3.0/hone.mcpb`
- Version: `0.3.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 13/100
  - Malware scan not yet available for this package.
  - CVE data not yet available for this package.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 100), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (Apache-2.0).
  - Actively maintained (last published 43 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 29/100
  - AI-judged instruction clarity (poor).
  - Context-footprint check failed: tool/resource definitions use about 991 tokens (~247/item across 4 items; 4 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 86/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 59% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

- Download bundle: `https://github.com/derekchoyai/hone/releases/download/v0.3.0/hone.mcpb`

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 36, +13)

- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Stability: unverified → 0.23
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Schema quality: unverified → poor

### 2026-08-01 (score 23, +10)

- [functional regression] Dependency health: partial → unverified
- [functional improvement] Tool coverage: unverified → 100

### 2026-07-31 (score 13, −19)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 32, +2)

- [functional improvement] Maintenance: unverified → pass

### 2026-07-28 (score 30, −2)

- [functional regression] Maintenance: pass → unverified

### 2026-07-27 (score 32)

First indexed and scored.

## MCP tools (4)

### `get_protocol` (~279 tokens)

Get the open AI-Q standard protocol for computing the user's AI-Q (their judgment over AI-assisted work — the three Ds: Discernment, Delegation, Design) in YOUR context. mode='after' (default) reviews FINISHED AI-assisted work: dimension definitions, domain rubric, interview rules (incl. the delegation probe), question count, techniques, deterministic scoring, and the report + teaching (3-5 lessons) structure. mode='during' is THINK-FIRST — Delegation coaching: the user has not produced anything yet; sharpen their prompt and prime their judgment BEFORE the AI answers (no Discernment score exists yet). You (the host model) already have the work/task loaded — you do the reading and run the interview; this tool supplies the methodology. Call this BEFORE interviewing the human.

Input parameters:

- `context` (string): Who/where: adapts language, tone, depth, and the scoring bar.
- `domain` (string, required): The kind of work being reviewed (or the task domain in think-first mode).
- `mode` (string): 'after' = review finished work (default, scored). 'during' = think-first: prime judgment before using AI (not scored).
- `riskLevel` (string): low = throwaway; medium = shared/internal; high = production, money, health, legal, irreversible.

### `score_review` (~285 tokens)

Deterministically score a completed AI-Q judgment interview into the user's AI-Q. Pass the six 1-5 Discernment dimension scores (judged by comparing the human's answers to your private work map), and — ONLY if your interview surfaced the brief/iteration history — the three 1-5 Delegation facets. Returns the official AI-Q composite (0-100, weights renormalized over what was assessed), band, sub-scores, and calibration read. For a think-first delegation-only read, pass just the three facets. ALWAYS use this instead of computing any score yourself.

Input parameters:

- `accountability`
- `assumptionAwareness`
- `briefQuality`: 1-5 — Delegation: did the brief carry the context, constraints, and success criteria the task needed? Pass ONLY with evidence from the interview.
- `confidenceCalibration`
- `iterationControl`: 1-5 — Delegation: caught and corrected drift between first output and final. Pass ONLY with evidence.
- `riskRecognition`
- `statedConfidence` (number): The 0-100 confidence the human stated BEFORE seeing any results.
- `taskSelection`: 1-5 — Delegation: right task to hand to AI; knew what to keep human. Pass ONLY with evidence.
- `understanding` (number): 1-5
- `verification`

### `record_review` (~335 tokens)

Save a completed judgment review to the user's LOCAL profile (~/.hone/profile.json) — judgment METADATA ONLY (scores, domain, a short subject label), never the work itself. Pass the six Discernment dimensions, plus the three Delegation facets when assessed; a think-first delegation read passes just the facets. All sub-scores and the AI-Q composite are recomputed server-side (passed composites are ignored — anti-gaming). Future get_protocol calls personalize from this history. Returns the updated trend and an encouragement read. Tell the user you're saving scores only, and skip this call if they decline.

Input parameters:

- `accountability`
- `assumptionAwareness`
- `briefQuality`: 1-5 — Delegation facet; pass ONLY when assessed behind the evidence gate.
- `confidenceCalibration`
- `context` (string)
- `domain` (string, required): The kind of work that was reviewed.
- `iterationControl`: 1-5 — Delegation facet; pass ONLY when assessed.
- `riskLevel` (string)
- `riskRecognition`
- `statedConfidence` (number): The 0-100 confidence the human stated BEFORE the reveal.
- `subject` (string): ≤8-word neutral label of WHAT was reviewed (e.g. 'Q3 GTM strategy deck') — a recall anchor, never the content.
- `taskSelection`: 1-5 — Delegation facet; pass ONLY when assessed.
- `topGap` (string): One short sentence: the single most important gap from this review.
- `understanding` (number): 1-5
- `verification`

### `get_profile` (~92 tokens)

The user's longitudinal AI-Q profile from this machine's local history (~/.hone/profile.json): review count, per-dimension Discernment averages, weakest/strongest dimension, composite and calibration trends, Delegation stats when assessed, qualitative Design indicators, and recent reviews. Use it to answer 'how is my judgment developing?' or to ground coaching in their actual history. Contains judgment metadata only — never any reviewed work.

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb#diagnostics

## Score history

- 2026-08-03: 36
- 2026-08-02: 36
- 2026-08-01: 23
- 2026-07-31: 13
- 2026-07-30: 32
- 2026-07-28: 30
- 2026-07-27: 32

## Links

- Repository: https://github.com/derekchoyai/hone
- Changelog RSS feed: https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb/changelog.json
- HTML version of this page: https://verifymcp.io/servers/derekchoyai-hone/https-github-com-derekchoyai-hone-releases-download-v0-3-0-hone-mcpb