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experiment-analyze

The EVALUATE stage of the research loop.

Skill by Shiien

IndexedMIT★ 7
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/shiien-experiment-analyze

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About

The EVALUATE stage of the research loop. Judges experiment results against the pre-registered contract (never against post-hoc criteria), classifies the outcome as supporting/contradicting/inconclusive evidence with a strength stamp, and persists the verdict to RESEARCH_STATE.md and EXPERIMENTS.json. Triggers when the user shares training logs, metrics, or asks "what do these results mean?", "are these results good?", or auto-chains after experiment-monitor reports completion.

Use cases: documents, research

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/experiment-analyze

What's inside

Skill name
experiment-analyze
Description
The EVALUATE stage of the research loop. Judges experiment results against the pre-registered contract (never against post-hoc criteria), classifies the outcome as supporting/contradicting/inconclusive evidence with a strength stamp, and persists the verdict to RESEARCH_STATE.md and EXPERIMENTS.json. Triggers when the user shares training logs, metrics, or asks "what do these results mean?", "are these results good?", or auto-chains after experiment-monitor reports completion.
License
MIT
Instructions
55 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# experiment-analyze

**Trigger**: User shares experiment results, training logs, or metrics; asks
"what do these results mean?"; or an external run reaches `completed`.

**Principle**: an experiment is complete only when this stage has run.
Judgment happens against criteria written BEFORE the result existed.

**Process**:
1. **Retrieve the contract** for this run: `runs/<id>/contract.yaml` (harness
   runs — prefer `python -m harness evaluate <run>`, which is deterministic
   and tamper-checked), `logs/experiments/{exp_id}.yaml § contract`, or
   `experiments/{exp_name}/plan.md § Contracts`. If no contract exists, say
   so explicitly: the analysis is then EXPLORATORY and may generate
   hypotheses but not evidence — offer to write a contract for a
   confirmatory rerun.
2. **Parse the results** (tables, metrics, W&B, logs). Check
   `required_diagnostics` exist; missing diagnostics → inconclusive.
3. **Judge deterministically** against `success_metric` /
   `failure_condition`: prefer computed comparisons (mean ± std over seeds,
   tests, invariants) over prose judgment. Keep `dev.*` and `confirm.*`
   metrics separate; a claim confirmed only on dev metrics is not confirmed.
4. **Guardrails** (from `CLAUDE.md § Evaluation Guardrails`):
   - a crash/NaN/OOM is a failure record, NOT negative evidence — route to
     `code` (debug mode) / resume instead of a verdict;
   - single noisy runs get `strength: weak (n=1)` — never "shows" or
     "proves";
   - if the observed result makes a different criterion look more
     appropriate, record the pre-registered verdict FIRST, then propose the
     new criterion as a new experiment.
5. **Persist the evidence** (this step is not optional):
   - `RESEARCH_STATE.md § Established evidence`: `[date] {exp/run id}:
     SUPPORTS/CONTRADICTS — {question} | {criterion detail} | strength: {stamp}`;
     inconclusive outcomes go to `§ Unresolved uncertainties` with what would
     sharpen them.
   - `EXPERIMENTS.json`: set `status`, `run`, `verdict` on the ledger entry.
   - If this is the hypothesis's **second consecutive `inconclusive`**
     verdict, don't queue a third unchanged rerun: propose a narrower
     hypothesis (tighter contract) or mark it `terminated`. When evidence
     clears the bar either way, annotate `§ Active hypotheses` with
     `[decision: supported|falsified, date, evidence ref]` (`CLAUDE.md §
     Hypothesis Closure & Scope Discipline`) — don't leave a decided
     hypothesis looking still-open.
6. **Propose the next experiment**: the cheapest run that resolves the
   sharpest remaining uncertainty, one conceptual factor changed. Append to
   `§ Next recommended experiments`.

**Inputs**: results + the pre-registered contract
**Outputs**: verdict + updated `RESEARCH_STATE.md` / `EXPERIMENTS.json`; analysis inline
**Token**: ~3-8K
**Composition**: supported core claim → `writing` (draft mode) + `checklist`
(update mode); contradicted → `decision-analyze`; crashed → `code` (debug mode);
inconclusive → `experiment-plan` for a sharper contract.

From Shiien/Self-Evolved-Research-Framework, MIT.

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Last commit (this folder)
Jul 14, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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experiment-analyze skill. Agent Mart. https://agentmart.dev/skills/shiien-experiment-analyze (last updated 2026-10-24)