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Research · Version 1.2.0 · Reviewed 2026-08-02

Research Evidence Gatherer

Produce defensible evidence for research source plan and evidence corpus assembly with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Builds a bounded evidence corpus from source code, documents, history, external references, and negative cases. It grounds the decision in the research question, decision deadline, source boundaries, repositories, documents, history, and disconfirming evidence and explicitly prevents collecting only sources that support the initial hypothesis or losing provenance while summarizing large evidence sets.

₹199 one-time

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What this skill helps you do

  • Research source plan
  • Evidence corpus assembly
  • Source reliability assessment

How Research Evidence Gatherer works

You provide

Sources, method notes, and the question being answered

It inspects

Evidence strength and negative cases for research source plan

It decides

A evidence corpus assembly synthesis with limitations named

You verify

Findings reproducible from the cited evidence alone

What it checks first

Research Evidence Gatherer builds a bounded evidence corpus from source code, documents, history, external references, and negative cases. It grounds the decision in the research question, decision deadline, source boundaries, repositories, documents, history, and disconfirming evidence and explicitly prevents collecting only sources that support the initial hypothesis or losing provenance while summarizing large evidence sets. Use it when the work involves Research source plan, Evidence corpus assembly, Source reliability assessment.

  1. Sample size, selection method, and who was excluded, since these bound every conclusion.
  2. Whether a finding is supported by observed behavior or by what participants said they would do.
  3. Disconfirming cases, which are the fastest test of whether a theme is real.
  4. Whether the question the research answers is the question the decision actually needs.

Failure modes it recognizes

  • Themes derived from the loudest participants rather than from the sampled distribution.
  • Leading questions producing agreement that disappears under neutral phrasing.
  • Survivorship bias from studying only current customers or successful accounts.
  • Coding drift where the same excerpt would be categorized differently later in the process.

Answers it will reject

  • Reporting percentages from a small qualitative sample, which implies precision that does not exist.
  • Treating a synthesized theme as a finding without the excerpts that support it.
  • Stopping at the first pattern that confirms the pre-existing hypothesis.

Decision rules it applies

  • State the sample, the method, and the limitation alongside every finding.
  • Actively seek disconfirming evidence before accepting a theme.
  • Separate what was observed, what was reported, and what was inferred.

Evidence it asks for

  • Attach verbatim excerpts to each theme so a reader can audit the interpretation.
  • Check coding consistency by re-coding a subset and comparing.
  • Report counts with denominators rather than percentages alone.

The method inside

  1. Define the research question and unit of analysis
  2. Create a transparent coding or extraction framework
  3. Preserve source traceability and negative evidence
  4. Separate findings, interpretation, limitations, and applicability

Deliverables

  • Research source plan evidence table
  • Evidence corpus assembly findings with negative cases
  • Source reliability assessment limitations and next-research plan

Evidence requirements

  • Source documents, transcripts, data, and research question
  • Sampling method, population, and collection context
  • Known limitations, contradictory cases, and analysis criteria

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Apply the research evidence gatherer to our current research source plan work. We need a concrete decision, bounded changes, and evidence that the result is correct.

Expected output

Start with the research question, decision deadline, source boundaries, repositories, documents, history, and disconfirming evidence. The highest-risk failure is collecting only sources that support the initial hypothesis or losing provenance while summarizing large evidence sets. Stop when the decision-changing claims have corroboration, negative cases, and known uncertainty. Verify the result by resolving every claim to an immutable source and having another reader reproduce the evidence selection.

Boundaries and compatibility

Ideal for

  • Research source plan: produce a decision or artifact grounded in supplied evidence.
  • Evidence corpus assembly: produce a decision or artifact grounded in supplied evidence.
  • Source reliability assessment: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Fabricating sources, participants, or findings
  • Claiming representativeness without a sampling basis

Agent compatibility

  • GitHub Copilot Agent Skills
  • Cursor Agent Skills
  • Claude Code Skills
  • OpenAI Codex Skills
  • JetBrains Junie Skills

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.