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Research · Version 1.1.0 · Reviewed 2026-08-02

Documentation Insight Miner

Produce defensible evidence for documentation gap mining and design rationale extraction with evidence, explicit trade-offs, and a verification plan.

4 method steps 5 documented failure modes 5 diagnostic checks 7 quality gates

Extracts missing rationale, recurring confusion, and undocumented constraints from engineering discussions and change history. It grounds the decision in pull requests, issue discussions, incidents, support questions, decision records, and existing documentation and explicitly prevents promoting one comment into a universal rule without corroboration across code, owners, or repeated failures.

₹199 one-time

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What this skill helps you do

  • Documentation gap mining
  • Design rationale extraction
  • Tribal knowledge capture

How Documentation Insight Miner works

You provide

The reader task, current pages, source evidence, navigation, and support or search signals

It inspects

Correctness, findability, and task completion for documentation gap mining

It decides

A design rationale extraction change with ownership and a refresh trigger

You verify

A clean reader completes the task and the documentation build validates links, metadata, and examples

What it checks first

Documentation Insight Miner extracts missing rationale, recurring confusion, and undocumented constraints from engineering discussions and change history. It grounds the decision in pull requests, issue discussions, incidents, support questions, decision records, and existing documentation and explicitly prevents promoting one comment into a universal rule without corroboration across code, owners, or repeated failures. Use it when the work involves Documentation gap mining, Design rationale extraction, Tribal knowledge capture.

  1. The user task the document must enable and the observable completion condition, rather than the page type alone.
  2. Technical claims traced to current code, configuration, interfaces, or an accountable decision owner.
  3. Navigation and search language aligned with how readers describe the problem instead of the owning team structure.
  4. Executable examples tested in a clean environment with the same versions and prerequisites the page declares.
  5. Ownership, last-reviewed evidence, and a refresh trigger tied to the source behavior most likely to change.

Failure modes it recognizes

  • A correct page remains undiscoverable because its title and navigation use internal vocabulary readers never search.
  • Setup instructions omit an implicit credential, platform, or working-directory assumption and fail on the first command.
  • Documentation describes the intended architecture while production code follows a later undocumented path.
  • Generated navigation excludes a valid page or keeps a deleted page reachable through stale links.
  • A support answer is copied into documentation without verifying that the workaround remains safe and current.

Answers it will reject

  • Measuring documentation quality by page count, word count, or formatting compliance instead of task success.
  • Mirroring the repository tree as navigation when readers approach the system by goals and failures.
  • Publishing code samples that were syntax-checked but never executed against the stated prerequisites.
  • Adding an FAQ entry for every support question instead of repairing the earliest missing concept or task step.

Decision rules it applies

  • Fix incorrect and task-blocking content before improving completeness, style, or visual polish.
  • Prefer one maintained source for a fact and link to it rather than duplicating volatile instructions across pages.
  • Create a new page only when it owns a distinct reader task or decision and has a durable maintenance owner.
  • Retire content when no current reader journey depends on it or when a maintained source supersedes it completely.

Evidence it asks for

  • Run links, metadata, navigation generation, and representative code examples in the documentation build.
  • Trace support and search queries to the page and section where the reader task currently fails.
  • Test the highest-value journeys from a clean environment using only the published instructions.
  • Diff documented commands, interfaces, and configuration against their defining source at release time.

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

  • Documentation gap mining evidence table
  • Design rationale extraction findings with negative cases
  • Tribal knowledge capture 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 documentation insight miner to our current documentation gap mining work. We need a concrete decision, bounded changes, and evidence that the result is correct.

Expected output

Start with pull requests, issue discussions, incidents, support questions, decision records, and existing documentation. The highest-risk failure is promoting one comment into a universal rule without corroboration across code, owners, or repeated failures. Capture knowledge only when it changes future decisions and attach confidence, scope, and durable evidence. Verify the result by having an accountable owner confirm the extracted rationale and linking it to the maintained documentation surface.

Boundaries and compatibility

Ideal for

  • Documentation gap mining: produce a decision or artifact grounded in supplied evidence.
  • Design rationale extraction: produce a decision or artifact grounded in supplied evidence.
  • Tribal knowledge capture: 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.