SkillAgentSearch skills...

crucible

Python and MCP tools for testing falsifiable claims and recording MATCH, DRIFT, or UNVERIFIABLE outcomes against supplied evidence.

Install / Use

claude mcp add HarperZ9 -- npx -y github:HarperZ9/crucible

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

83/100

Supported Platforms

Claude Code
Claude Desktop

Our assessment of crucible

crucible scores 83/100 on our quality scale, 411th of 705 AI & Machine Learning skills we index.

Its MCP Server is 14 KB long, well organised into 12 sections with 10 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
3/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so crucible is actively maintained.
  • Our last check on 2026-09-12 found the source still online.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 80/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

crucible compared with similar skills

All 4 of these similar skills score higher than crucible; compare them before choosing.

SkillScoreStarsUpdatedFormat
crucible (this skill)by HarperZ98338d agoMCP Server
claude-memby thedotmack10094.7ktodayCLAUDE.md
Agent-Reachby Panniantong10085.5k11d agoCLAUDE.md
Understand-Anythingby Egonex-AI10084.2k14d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md

Frequently asked questions

How do I install crucible?
Run claude mcp add HarperZ9 -- npx -y github:HarperZ9/crucible. The install tabs above show the steps for each supported agent.
Which AI agents does crucible work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is crucible safe to use?
Our scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 80/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is crucible still maintained?
The repository was last updated 8 days ago, so crucible is actively maintained.
<p align="center"><img src=".github/assets/zentropy-banner.png" alt="crucible: A judgment engine: register a thesis, steelman each claim, measure against a substrate, refine the weakest axis." width="100%"></p>

A judgment engine: register a thesis, steelman each claim, measure against a substrate, refine the weakest axis.

PyPI license: crucible Fair-Source CI downloads python: 3.11+ deps: none (core)

crucible turns a thesis into a set of claims, each paired with the observation that would refute it. Independent adversaries steelman every claim by proposing the strongest test, the engine measures each one against a substrate oracle, and the weakest axis gets refined across rounds: strengthen the substrate, sharpen the measurement, or amend the thesis. The result is a verdict per claim, MATCH, DRIFT, or UNVERIFIABLE, grounded in the measurement rather than a judge's opinion. Every run writes a record you can re-check.

Project Telos | gather | crucible | index | forum | telos | learn | emet | buildlang

Highlights

  • Verdicts that recompute from the record. verdict_for(claim, measurement) is a pure function: within tolerance is MATCH, outside is DRIFT, absent or unmeasurable is UNVERIFIABLE, fail-closed. No model sits in the verdict step, so a fluent assertion cannot move a rechecked result.
  • One-command runs with cleanroom review packets. crucible run --bundle DIR executes steelman, measurement, witnessed assessment, and disk recheck in one session, then writes a self-contained verifier packet (spec.json, run.json, report.md, review.md). crucible review DIR validates the packet boundary before handoff.
  • A CI regression check. crucible ci compares a registry's verified-latest verdicts against a sealed baseline, exits nonzero when any claim loses standing, and emits a deterministic PR-comment Markdown matrix. New in 1.2.0.
  • A refine loop that names the weakest claim. Grade each claim's measured margin, compute harmonic-mean cohesion, and re-measure across substrate rounds until the thesis is cohesively verified or the budget is spent. The loop reports the weakest axis instead of pretending a short thesis held.
  • Drift tracking across rounds. crucible drift compares the latest two witnessed assessments and classifies each claim as held, moved, improved, or regressed.
  • LLM-as-judge with the model outside the verdict. JudgeMeasure scores freeform outputs against a rubric; the judge produces a deviation once at the seam, the verdict still derives from verdict_for, and a judge that raises or returns garbage fails closed. New in 1.2.0.
  • Oracle recheck packs. crucible recheck lists descriptor-bearing measurements, writes crucible.replay-template/1 templates, and validates crucible.replay-pack/1 inputs against the sealed rows without opening a second verdict path. A privacy-bounded crucible.replay-set/1 binding covers the descriptor-bearing replay contracts without exporting descriptorless rows or their evidence. CLI replay packs must preserve the template's assessment binding; a missing or mismatched thesis ID, assessment seal, or measurement seal fails closed before replay.
  • A content-addressed registry with tamper detection. Every claim carries a sha256 receipt; the registry re-verifies stored claims (MATCH / MISSING / CORRUPT), checks thesis seals, rejects duplicate ids with different seals, and refuses tampered theses.
  • Typed missing-evidence explanations. Every UNVERIFIABLE verdict names the exact evidence class it lacks and the concrete next action, derived from the same pure ladder as the verdict, so the explanation can never disagree with it. New in 1.2.0.
  • Batch manifests, Markdown reports, creative measurement gates, native MCP. crucible batch runs a manifest of theses into one registry, crucible report renders deterministic Markdown, crucible measurement-gate verifies Telos creative measurement packets, and crucible mcp serves 13 tools over stdio.
  • Zero third-party runtime dependencies. The core is pure standard library, Python 3.11+.

Install

pip install crucible-bench

The distribution is crucible-bench; it installs the crucible command and the crucible package (import crucible). For the examples and the newest commands, work from a clone:

git clone https://github.com/HarperZ9/crucible
cd crucible
pip install -e ".[dev]"

Quickstart

Run the bundled demo from a clone. It registers a three-claim thesis, steelmans it, assesses it, and then shows tampering being caught:

python examples/demo.py
thesis "Binary search comparison bounds": 3 claims, seal bd7404c02eb2...
  MATCH        deviation 0 within tolerance 0.5
  DRIFT        deviation 8 exceeds tolerance 0.5
  UNVERIFIABLE claim states no falsification condition
counts: MATCH 1  DRIFT 1  UNVERIFIABLE 1
assessment seal 07dafef03f5c..., verified True
after flipping a DRIFT to a MATCH, verified False  <- caught

Then run the same thesis through the full loop into a registry:

crucible run examples/thesis-binary-search.json \
  --measurements examples/measurements-binary-search.json \
  --registry .crucible-registry
ran thesis bd7404c02eb2036e: 3 claim(s)
  steelman refutations: 3
  MATCH 1  DRIFT 1  UNVERIFIABLE 1
  assessment seal: 62f928fe21052041...
  re-derived from disk: True  {'seals_ok': True, 'thesis_ok': True, 'verdicts_rederive': True}

Add --json for the machine-readable run record, --substrate examples/substrate-binary-search.json instead of --measurements to go through the table oracle, and --bundle DIR to write a cleanroom review packet. A visual verdict surface lives at examples/crucible-demo.html.

A worked example

A thesis is claims plus falsification conditions:

{
  "title": "Binary search comparison bounds",
  "disposition": "publishable",
  "claims": [
    {
      "text": "binary search over a sorted array of 1024 elements does at most 11 comparisons",
      "falsification": "a measured worst-case comparison count above 11 for n=1024"
    },
    {
      "text": "binary search is more elegant than linear search",
      "falsification": ""
    }
  ]
}

The first claim is measurable: a measurement row binds to it by content hash, records a deviation and a tolerance, and the verdict follows. The second claim states no falsification condition, so it is UNVERIFIABLE by construction, and the assessment says exactly which evidence class is missing. Run it, bundle it, and validate the packet:

crucible run thesis.json --measurements measurements.json \
  --registry .crucible-registry --bundle reports/my-run
crucible review reports/my-run

The bundle gives a verifier only the spec and the artifact, with packet-relative paths. review fails closed on missing files, extra context, a spec.json that drifted from the run record, or a report.md that no longer renders from run.json.

To gate pull requests on the registry:

crucible ci .crucible-registry --write-baseline crucible-baseline.json   # on a known-good commit
crucible ci .crucible-registry --baseline crucible-baseline.json --out crucible-ci.md

A regression is a claim moving MATCH to DRIFT, becoming UNVERIFIABLE, or dropping out of the verified-latest set. The baseline seals its own cells, so a hand-edited baseline is rejected on load. The Markdown summary is deterministic and references the assessment seal behind every cell.

Command surface

| Command | What it does | | --- | --- | | crucible run THESIS --measurements F \| --substrate F | full loop in one session; --bundle DIR writes a review packet | | crucible register / assess / steelman / measure | the individual loop stages | | crucible review BUNDLE | validate a cleanroom packet before verifier handoff | | crucible refine CONFIG | rounds of substrate refinement toward cohesive verification | | crucible drift DIR | classify claim movement between the latest two assessments | | crucible ci DIR | regression gate against a sealed baseline | | crucible recheck DIR | inspect, template, or replay oracle measurement descriptors | | crucible registry list\|verify\|stats\|search\|prune | registry operations, including --require-witnessed-match | | crucible verdicts DIR [--verify] | list or re-derive witnessed assessments | | crucible report DIR / crucible batch MANIFEST | Markdown reports; manifest runs into one registry | | crucible export THESIS | publication-gated export; fenced material is refused at the edge | | crucible measurement-gate PACKET | verify a Telos creative measurement packet | | crucible status / doctor / demo | operator envelope, readiness checks, demo pointer (--json) | | crucible mcp | serve the 13 crucible tools over MCP stdio |

Every command works identically from a source checkout via python -m crucible.

Extending the seams

The steelman and measure stages are seams with a stable API shape. Defaults are Null (propose nothing, measure nothing, UNVERIFIABLE), and the shipped edges include:

  • TableMeasure: offline deviation against a provided substrate table, no model.
  • SubprocessSteelman / SubprocessMeasure: configured commands over bounded JSON stdin/stdout, with timeouts, no shell strings, minimal environment, and output caps.
  • TelosMeasure: consumes telos.witnessed-artifact/v1 envelopes and re-runs the named verifier rather than trusting the carried certificate.
  • GatherDigestMeasure / IndexMeasure: sealed gather digests as evidence, and index.verification/1 records replayed against graph packs.
  • JudgeMeasure: rubric-scored LLM judging behind an injectable backend, deterministic stub in tests, null by default.
  • ProofMeasure: a proof or type checker (Lean, Coq, a type checker, any command) as the oracle for formal claims. It runs the checker over the claim's artifact: an accepted proof is MATCH, a rejected one DRIFTs, and a checker that is absent or errors is UNVERIFIABLE, fail-closed, so an unrun checker never reports a proof as holding. The measurement binds the exact command and the artifact hash, so a stranger replays the identical check. This is the oracle for the north star, verified discovery in math.

All edges map into the same Measurement to verdict_for spine. The verdict step never changes.

Documentation

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3
CategoryAI
Updated8d ago
Forks0

Languages

Python

Trust signals

80/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium1 low