🧪 Skills

bounded-researcher

Bounded evidence-first research workflow for software agents. Use when an agent should reduce uncertainty, localize issues, validate outputs, or summarize ev...

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Description


name: bounded-researcher description: Bounded evidence-first research workflow for software agents. Use when an agent should reduce uncertainty, localize issues, validate outputs, or summarize evidence without taking architecture ownership or editing production code.

Bounded Researcher

Use this skill when a research-oriented agent must stay tightly constrained and hand back the next bounded engineering step instead of drifting into open-ended analysis.

When To Use

Use for tasks like:

  • triage
  • localization
  • validation
  • summarization
  • narrow evidence gathering for engineering or review

Do not use for:

  • production code edits
  • final architecture decisions
  • unconditional tool or library adoption
  • unsupported license, compatibility, or quantitative claims

Operating Model

This skill assumes:

  • a separate supervisor or coordinator owns final decisions
  • the researcher reduces uncertainty rather than owning implementation
  • the agent should stop as soon as it can enable the next bounded step

Workflow

  1. Read the dispatch carefully.
  2. Classify the task:
    • triage
    • localize
    • validate
    • summarize
  3. Load only the minimum relevant context.
  4. Separate:
    • facts
    • inferences
    • unknowns
  5. Return the next bounded step.
  6. Escalate instead of guessing when the task drifts into implementation or architecture.

Evidence Priority

Use sources in this order:

  1. local code and project docs
  2. current task notes and runbook docs
  3. primary external documentation
  4. secondary sources only when primary sources are unavailable

Hard Rules

  • If license text is not directly verified, say license unverified.
  • If compatibility is not directly evidenced, mark it as unverified.
  • If numbers come from a source rather than local measurement, attribute them.
  • If evidence is mixed or weak, say so explicitly.
  • If the task expands, stop and return a narrower next step.
  • Do not convert a candidate option into an adopted decision.

Output By Task Class

triage

Return:

  • problem_summary
  • candidate_files
  • next_task
  • open_questions

localize

Return:

  • ranked_targets
  • evidence
  • confidence
  • do_not_touch

validate

Return:

  • commands_run
  • pass_fail
  • key_output
  • remaining_failures

summarize

Return:

  • inputs_used
  • summary
  • unknowns
  • recommended_next_step

Escalation Rules

Escalate when:

  • the evidence points to an architecture or interface change
  • more than 3 files likely need coordinated edits
  • the root cause is still unclear after one pass
  • the task now requires implementation rather than uncertainty reduction

Response Style

  • concise
  • evidence-first
  • explicit about uncertainty
  • optimized for the next engineering action

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Compatible Platforms

Pricing

Free

Related Configs