autoresearch

id	autoresearch
name	Autoresearch
version	2.0.0
layer	skill
runtime	nodejs
author	home23
description	Iteratively improve a weak skill through score, tweak, and retest loops. Run against a target skill, define failure mode and rubric, execute the loop, and get a scored report with recommendations.
category	meta
keywords	["skill","improve","autoresearch","optimize","iterate","quality"]
triggers	["improve this skill","autoresearch this skill","optimize the skill","why is this skill weak"]
capabilities	[{"autoresearch_loop":"Run a full score/tweak/retest loop against a target skill"}]
requiresTools	["skills_run","skills_list","skills_get","skills_audit"]
dependsOn	["skill-loader"]
composes	["knowledge-structuring","source-validation"]

Autoresearch

Use this skill when a skill exists but performs inconsistently and needs deliberate improvement rather than one-off fixes.

When to use

Use autoresearch for:

• a skill that triggers inconsistently across similar asks
• a skill whose instructions feel vague, brittle, or underspecified
• quality work where the target is the skill itself, not just the current answer

Workflow

1. Define the failure mode clearly.
2. Choose a score rubric (5 dimensions, 1–5 each).
3. Run representative prompts against the skill across N rounds.
4. Auto-revise SKILL.md after each round (targets weakest dimension).
5. Stop when score gain flattens (≤ 0.2 improvement).
6. Return a scored report with per-round results and recommendations.

Score Rubric (5 dimensions)

Dimension	What it measures
queryStrategy	Detects zero/low results and auto-broadens or retries
qualityFiltering	Filters spam, elevates high-engagement signal
resultCoverage	Gets meaningful result volume per query
actionContract	Returns well-formed, predictable responses
documentation	SKILL.md examples and gotchas are clear and actionable

Scores: 1 (broken) → 3 (functional) → 5 (excellent).

autoresearch_loop action

{
  "action": "autoresearch_loop",
  "input": {
    "targetSkill": "x-research",
    "failureMode": "X search returns spam for health queries with no retry logic",
    "promptSet": [
      "sauna cold plunge contrast therapy",
      "infrared sauna health benefits",
      "cold plunge recovery sleep"
    ],
    "scoreRubric": {
      "queryStrategy": { "target": 4 },
      "qualityFiltering": { "target": 3 },
      "resultCoverage": { "target": 3 },
      "actionContract": { "target": 4 },
      "documentation": { "target": 3 }
    },
    "maxRounds": 3
  }
}

Output

Returns a JSON report with:

• rounds[]: per-round scores per prompt and dimension averages
• summary: start/final/total gain, rounds run, stopped-early flag
• recommendations[]: dimensions still scoring < 3 after loop

Report saved to workspace/reports/autoresearch/autoresearch-{skill}-{timestamp}.json.

Gotchas

• Do not autoresearch every miss. Only use it when the pattern repeats.
• Keep the prompt set stable while you iterate or the score signal becomes noise.
• Fix routing text and gotchas before inventing more actions.
• Autoresearch runs inside the target skill's context — it does NOT need its own auth.
• Round scores start at ~2–3 for a broken skill and should climb with each revision.