Agent skill

Documentation Research Methodology

by prime-radiant-inc in prime-radiant-inc/greenfield

Method for extracting behavioral specifications from a product's public documentation: tiered search order, claim extraction rules, output structure, stop criteria and gap analysis.

Apache-2.0Auto-check passedDevelopment

Install Documentation Research Methodology

skills CLI
$ npx skills add prime-radiant-inc/greenfield --skill doc-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install prime-radiant-inc/greenfield doc-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/prime-radiant-inc/greenfield.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doc-research .claude/skills/doc-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
doc-research
GitHub stars
292
Token cost
~4.6k tokens
SKILL.md length
1,820 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
Apache-2.0

At a glance

Method for extracting behavioral specifications from a product's public documentation: tiered search order, claim extraction rules, output structure, stop criteria and gap analysis.

  • Works in 7 steps: Search Sequence → Fetching Rules → Extraction Methodology → …
  • Researching how a product behaves using only its public documentation
  • SKILL.md covers 1. Search Sequence, 2. Fetching Rules, 3. Extraction Methodology and 4. Output Structure, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

A step-by-step methodology, written as normative rules, for turning public documentation into behavioral claims about a product. Searching moves from the most to the least authoritative source, and every pattern in a tier must be run before the next tier starts. Tier 1 is official documentation, with twelve search patterns such as API reference, getting started, configuration, CLI reference, changelog, release notes, migration guide, FAQ, troubleshooting and security, then a traversal of the official site's navigation and pagination.

Tier 2 looks for machine-readable specifications that fit the product type: OpenAPI or Swagger files, GraphQL schemas, protobuf definitions, JSON schemas, man pages, help output and WSDL. The skill also defines claim extraction rules, an output structure, termination criteria and a gap analysis, but the excerpt ends before those sections and before the third tier. It is loaded by the analyzer agent of a plugin that builds behavioral specs.

When your agent uses it

  • Researching how a product behaves using only its public documentation
  • Collecting behavioral claims with sources from official docs, changelogs and release notes
  • Finding OpenAPI, GraphQL or protobuf specifications published for a product
  • Spotting gaps where the documentation does not describe a behavior

Example prompts

  • “Research the public documentation for Redis and extract its documented behavior claims, starting with the official docs.”
  • “Find any OpenAPI or GraphQL spec published for the Linear API.”
  • “Run a gap analysis on what the official docs for this CLI tool leave undocumented.”

Requirements

  • Web search and page fetching access

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Search Sequence
  2. Fetching Rules
  3. Extraction Methodology
  4. Output Structure
  5. Termination Criteria
  6. Gap Analysis
  7. Provenance Discipline

What it can do on your machine

Read from SKILL.md and the folder at commit 6e6d4b4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and dot).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Documentation Research Methodology loads about 4.6k tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 1,820 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from prime-radiant-inc/greenfield at commit 6e6d4b4, republished under its Apache-2.0 licence (© prime-radiant-inc). 1,820 words, ~4,625 tokens.

Download SKILL.mdSave it as .claude/skills/doc-research/SKILL.md (or your agent's skills folder).
name
doc-research
description
Public documentation extraction methodology. Search sequence (3 tiers), behavioral claim extraction rules, output structure, termination criteria, and gap analysis. Loaded by the analyzer agent for documentation research.

Documentation Research Methodology

This skill defines the complete methodology for extracting behavioral specifications from public documentation. Follow it step by step. Every section is normative.

1. Search Sequence

Search proceeds from most authoritative to least authoritative. Execute every pattern in each tier before moving to the next tier.

dot
digraph search_sequence {
    rankdir=TB;

    "Start documentation research" [shape=doublecircle];
    "Search Tier 1: Official documentation" [shape=box];
    "Traverse full official site structure" [shape=box];
    "Search Tier 2: Machine-readable specs" [shape=box];
    "Search Tier 3: Community knowledge" [shape=box];
    "Diminishing returns?" [shape=diamond];
    "Page budget exhausted?" [shape=diamond];
    "Write claims file and gaps file" [shape=box];
    "Run gap analysis by product type" [shape=box];
    "Research complete" [shape=doublecircle];

    "Start documentation research" -> "Search Tier 1: Official documentation";
    "Search Tier 1: Official documentation" -> "Traverse full official site structure";
    "Traverse full official site structure" -> "Search Tier 2: Machine-readable specs";
    "Search Tier 2: Machine-readable specs" -> "Search Tier 3: Community knowledge";
    "Search Tier 3: Community knowledge" -> "Diminishing returns?";
    "Diminishing returns?" -> "Write claims file and gaps file" [label="yes"];
    "Diminishing returns?" -> "Page budget exhausted?" [label="no"];
    "Page budget exhausted?" -> "Write claims file and gaps file" [label="yes"];
    "Page budget exhausted?" -> "Search Tier 3: Community knowledge" [label="no, continue"];
    "Write claims file and gaps file" -> "Run gap analysis by product type";
    "Run gap analysis by product type" -> "Research complete";
}
Tier 1: Official Documentation (source type: official-docs)

Execute these search patterns in order. Replace {product} with the target product name and {domain} with the official domain if known.

#Search PatternPurpose
1{product} documentationMain documentation site
2{product} API referenceAPI surface
3{product} getting startedInstallation, first run, quick setup
4{product} configuration referenceConfig files, keys, defaults
5{product} CLI referenceCommands, flags, arguments
6{product} changelogVersion history, behavioral changes
7{product} release notesFeature additions, breaking changes
8{product} migration guideVersion-to-version behavioral differences
9{product} FAQCommon behavioral questions and answers
10{product} troubleshootingError conditions and resolutions
11{product} securityAuth, encryption, permissions
12site:{domain} {product}Catch pages not found by keyword search

After finding the official documentation site, traverse its full structure:

  • Fetch the table of contents, sitemap, or sidebar navigation.
  • Queue every linked page that has not already been fetched.
  • Follow "next page" and pagination links.
Tier 2: Machine-Readable Specifications (source type: official-docs)

Execute the patterns relevant to the target product type. Not all patterns apply to all products.

#Search PatternApplies When
1{product} openapi or {product} swaggerProduct has a REST API
2{product} graphql schemaProduct has a GraphQL API
3{product} protobuf or {product} grpcProduct uses protocol buffers
4{product} json schemaProduct defines data formats
5{product} man pageProduct is a CLI tool on Unix
6{product} --helpProduct is a CLI tool
7{product} wsdlProduct has a SOAP API

Machine-readable specs are higher value than prose because they are precise and unambiguous. When a machine-readable spec exists, it takes precedence over prose documentation for the same topic.

Tier 3: Community Knowledge (source type: community-knowledge)
#Search PatternPurpose
1{product} site:stackoverflow.comCommunity Q&A about behavior
2{product} site:github.com discussionsMaintainer and community discussions
3{product} blog (filter for maintainer blogs)Design rationale, behavioral explanations
4{product} tutorial (filter for expert content)Practical behavioral descriptions

Community sources are valuable for:

  • Behaviors that official docs fail to document
  • Edge cases discovered by users
  • Practical workarounds that reveal behavioral constraints
  • Corroborating claims from official docs (upgrades confidence to confirmed)

Community sources are NOT authoritative for:

  • Exact parameter values or limits (may be outdated)
  • Version-specific behavior (community content may describe a different version)
  • Internal implementation details (community speculation is not evidence)
Prioritization

When the same behavioral information appears in multiple sources, prefer:

  1. Official API reference over tutorials
  2. Latest version documentation over older versions
  3. Machine-readable specifications over prose
  4. Maintainer content over community content
  5. Specific documentation (configuration reference) over general documentation (overview)

2. Fetching Rules

Rate Limiting
  • Insert at least 2 seconds between consecutive fetches to the same domain.
  • On HTTP 429, respect the Retry-After header. If no header is present, wait 30 seconds.
  • Maximum 3 retries per URL. After 3 failures, record the URL in gaps.md and move on.
Content Handling
  • Convert fetched HTML to markdown for storage.
  • Merge multiple pages about the same topic into a single raw file (e.g., a multi-page API reference becomes one api-reference.md).
  • Track visited URLs to avoid cycles in linked documentation.
  • If a page yields empty or skeleton-only content (likely JavaScript-rendered), record it in gaps.md with the note "dynamic rendering -- content not extractable via WebFetch."
Pages to Skip
  • Pages requiring authentication: record URL and auth type in gaps.md.
  • Pages in non-English languages: record URL and language in gaps.md.
  • Pages clearly outside the target product scope (e.g., unrelated products on the same domain).
  • Marketing and sales pages with no behavioral content.
Page Budget

Default limit: 50 pages per agent run. Prioritize Tier 1 official reference pages. If the budget is exhausted before all pages are fetched, record remaining URLs in gaps.md for a follow-up run.

3. Extraction Methodology

3.1 What Constitutes a Behavioral Claim

A behavioral claim is a statement that asserts something observable about the target's behavior. You are extracting these from prose and converting them into structured, citable claims.

Extract these claim types:

Claim TypeWhat to Look ForExample
Action-response"When you do X, Y happens"Running init creates a config file at ~/.tool/config.json
Data formatJSON schemas, field names, types, structuresResponse body contains {"id": string, "status": enum}
Constraint/limitMaximums, minimums, quotas, restrictionsFile uploads limited to 100MB
Default valueWhat happens when the user does not configure somethingDefault timeout is 30 seconds
Error conditionWhat triggers an error and what the error looks likeNon-existent resource returns HTTP 404 with {"error": "not_found"}
State transitionHow the system moves between statesSession moves from active to expired after 24 hours of inactivity
Execution sequenceOrdering guarantees, step-by-step processesAuthentication check runs before authorization check
Configuration effectWhat a config option changes about behaviorSetting DEBUG=true enables verbose logging to stderr
Algorithm/processingHow the system transforms dataPasswords are hashed using bcrypt with cost factor 12
Timing valueTimeouts, intervals, durations, TTLsRate limit resets every 60 seconds

Skip these non-claims:

SkipWhyExample
Marketing copyNot behavioral"Best-in-class performance"
Vague descriptionsNot testable"Robust security features"
Future plansNot current behavior"We plan to add WebSocket support"
Design motivationInformational, not normative"We chose this approach because..."
HistoryInformational"In previous versions, this worked differently"
Redundant restatementsAlready extractedSame claim restated in tutorial after being extracted from API reference
3.2 Normative vs. Informational Content

Documentation contains both normative content (what the product DOES) and informational content (context, history, motivation). Extract only normative content.

Normative indicators -- EXTRACT:

  • Imperative statements: "The API returns...", "The command creates..."
  • Requirement keywords: "must", "always", "never", "requires"
  • Concrete values: numbers, file paths, field names, status codes
  • Input/output descriptions: "Given X, the output is Y"
  • Code examples with expected output

Informational indicators -- SKIP:

  • Motivation: "We designed this because..."
  • History: "In version 1.x, this worked differently..."
  • Comparisons: "Unlike other tools, we..."
  • Opinions: "This is the recommended approach"
  • Aspirations: "We aim to provide..."
3.3 Handling Contradictions

When two documentation pages state different things about the same behavior:

  1. Record both claims. Each gets its own provenance citation.
  2. Flag the contradiction with an inline annotation:
    markdown
    - Default timeout is 30 seconds
      <!-- cite: source=official-docs, ref=https://docs.example.com/config#timeout, confidence=inferred, agent=doc-researcher -->
      <!-- contradiction: https://docs.example.com/quickstart claims 60 seconds -->
  3. Prefer the more specific source. Configuration reference beats quickstart guide. API reference beats tutorial. Changelog beats overview.
  4. Report in gaps.md. Contradictions are documentation gaps -- the docs are internally inconsistent.
Show full SKILL.md (738 more words)Show less
3.4 Handling Version-Specific Content
  1. Identify the documentation version from version selectors, URL path segments (/docs/v2/), or version badges.
  2. When the documentation version differs from the target version, mark affected claims as inferred and add a note: "documented for v{X}, target is v{Y}."
  3. When no version is stated, assume latest version. Note this assumption.
  4. Check changelogs between documentation version and target version for behavioral changes that would invalidate claims.
3.5 Deduplication

When the same behavioral claim appears on multiple pages:

  • Keep one entry in the claims file.
  • Cite the most authoritative source (API reference over tutorial).
  • If both sources are equally authoritative and agree, cite either and add corroborated_by to escalate confidence.

4. Output Structure

4.1 Raw Files (workspace/public/docs/raw/)

One file per topic area. Multiple pages about the same topic merge into one raw file.

markdown
# {Topic Name}

## Source
- **URL:** {primary source URL}
- **Additional URLs:** {other pages merged into this file}
- **Fetched:** {ISO 8601 timestamp}
- **Doc version:** {version if identifiable, otherwise "assumed latest"}

## Content Summary

[Concise structured extraction of key information from this topic area.
NOT verbatim reproduction. Organized by subtopic.]

## Key Behavioral Claims

- {claim text}
  <!-- cite: source=official-docs, ref={URL}#{section}, confidence={level}, agent=doc-researcher -->

- {claim text}
  <!-- cite: source=official-docs, ref={URL}#{section}, confidence={level}, agent=doc-researcher -->
4.2 Claims File (workspace/public/docs/claims/claims-by-topic.md)

The primary output. All behavioral claims organized by topic with full provenance.

markdown
# Behavioral Claims from Public Documentation

## Metadata
- **Target:** {product name}
- **Agent:** doc-researcher
- **Date:** {ISO 8601}
- **Total claims:** {count}
- **By confidence:** confirmed: {n}, inferred: {n}, assumed: {n}
- **Sources consulted:** {n} documentation pages, {n} community resources

---

## {Topic Area 1}

### CLAIM-DOC-001: {Short Descriptive Title}
{One or two sentences stating the behavioral claim precisely.}
<!-- cite: source={source-type}, ref={URL}, confidence={level}, agent=doc-researcher -->

### CLAIM-DOC-002: {Short Descriptive Title}
{Claim text.}
<!-- cite: source={source-type}, ref={URL}, confidence={level}, agent=doc-researcher -->

---

## {Topic Area 2}

### CLAIM-DOC-003: {Short Descriptive Title}
{Claim text.}
<!-- cite: source={source-type}, ref={URL}, confidence={level}, agent=doc-researcher -->

Claim ID format: CLAIM-DOC-{NNN} where NNN is a zero-padded three-digit sequence. IDs are assigned in the order claims are written and are never reused.

4.3 Gaps File (workspace/public/docs/gaps.md)
markdown
# Documentation Gaps

## Metadata
- **Target:** {product name}
- **Agent:** doc-researcher
- **Date:** {ISO 8601}
- **Topics documented:** {n}
- **Topics expected but missing:** {n}

---

## Missing Documentation

### GAP-001: {Topic}
**Expected:** {what documentation should exist for this topic}
**Found:** {what was actually found, or "No documentation found"}
**Impact:** {what analysis mode or manual effort could fill this gap}

---

## Authenticated Documentation (Skipped)

| URL | Auth Type | Notes |
|-----|-----------|-------|

## Non-English Documentation (Skipped)

| URL | Language | Notes |
|-----|----------|-------|

## Unfetched Pages (Budget Exhausted)

| URL | Reason | Priority |
|-----|--------|----------|

## Documentation Contradictions

| Topic | Page A | Page B | Contradiction |
|-------|--------|--------|---------------|

5. Termination Criteria

Stop the research process when ALL of the following are true:

  1. Official site exhausted. The official documentation site has been fully traversed -- all pages in the table of contents or sitemap have been fetched, or the page budget has been reached.
  2. All Tier 1 patterns executed. Every search pattern in Tier 1 has been run.
  3. Tier 2 attempted. At least 3 relevant Tier 2 patterns have been tried.
  4. Community reviewed. At least the top 5 Stack Overflow results have been reviewed.
  5. Diminishing returns. No new behavioral claims have been extracted from the last 3 pages fetched.

If the page budget (50 pages) is reached before these criteria are met, stop fetching but still write the claims and gaps files from what was gathered. Record the unmet criteria in gaps.md.

6. Gap Analysis

After all extraction is complete, assess documentation completeness by comparing what you found against what a complete documentation suite should include for the target product type.

Expected Topics by Product Type

CLI tool:

  • Installation and setup
  • All commands and subcommands
  • All flags and arguments (including global flags)
  • Configuration file format and location
  • Environment variables
  • Authentication and credentials
  • Error messages and exit codes
  • Input/output formats
  • Shell completion

Web API / REST service:

  • Authentication and authorization
  • All endpoints (method, path, parameters, request/response body)
  • Rate limiting
  • Pagination
  • Error response format and error codes
  • Versioning strategy
  • Webhooks (if applicable)
  • SDKs and client libraries

Library / SDK:

  • Installation
  • Public API surface (classes, functions, types)
  • Configuration and initialization
  • Error handling patterns
  • Lifecycle and resource management
  • Thread safety / concurrency model
  • Compatibility matrix (language versions, platforms)

Desktop / mobile application:

  • Installation and system requirements
  • Features and UI flows
  • Keyboard shortcuts
  • File formats
  • Configuration and preferences
  • Integration points (plugins, extensions, APIs)

For each expected topic that is missing or insufficiently documented, create a GAP entry in gaps.md. Note which other intelligence source (SDK analysis, runtime observation, source code analysis) could fill the gap.

7. Provenance Discipline

This section restates the rules from the provenance-methodology skill as they apply specifically to documentation research. Follow both this section and the full provenance-methodology skill.

Cite As You Go

Every time you write a behavioral claim, the very next thing you write is the citation. Do not batch citations. Do not defer them. Write the claim, write the citation, then move on.

Citation Format
markdown
<!-- cite: source={source-type}, ref={URL}, confidence={level}, agent=doc-researcher -->
Source Type Selection
  • Use official-docs for: official documentation pages, README files, man pages, API references, changelogs, published standards, RFCs
  • Use community-knowledge for: Stack Overflow answers, GitHub Discussions, third-party blog posts, tutorials by non-maintainers, conference talks
Confidence Assignment
  • confirmed: Two or more independent sources agree on the same behavioral claim. Example: official docs state a timeout is 30 seconds AND a Stack Overflow answer with maintainer confirmation says the same.
  • inferred: One authoritative source states the claim and nothing contradicts it. This is the most common confidence level for doc-researcher output.
  • assumed: No direct source states this, but it follows from convention or reasoning. Rare for this agent. If you find yourself writing many assumed claims, you may be speculating rather than extracting.
Standards and RFCs

When official documentation references a standard or RFC:

  • Note the standard name and relevant section numbers in the claim.
  • Use source type official-docs (the documentation itself is the source; the standard is additional context).
  • If you fetch the standard/RFC directly, cite it separately.

© prime-radiant-inc, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/doc-research of prime-radiant-inc/greenfield.

Open the folder on GitHubat commit 6e6d4b4

Compare with similar skills

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Questions about Documentation Research Methodology

What does Documentation Research Methodology do?

Method for extracting behavioral specifications from a product's public documentation: tiered search order, claim extraction rules, output structure, stop criteria and gap analysis. A step-by-step methodology, written as normative rules, for turning public documentation into behavioral claims about a product. Searching moves from the most to the least authoritative source, and every pattern in a tier must be run before the next tier starts.

When should I use Documentation Research Methodology?

Documentation Research Methodology fits situations like: researching how a product behaves using only its public documentation; collecting behavioral claims with sources from official docs, changelogs and release notes; finding OpenAPI, GraphQL or protobuf specifications published for a product; spotting gaps where the documentation does not describe a behavior.

How do I install Documentation Research Methodology in Claude Code?

Run `npx skills add prime-radiant-inc/greenfield --skill doc-research -a claude-code`. Or copy the skill folder (skills/doc-research in prime-radiant-inc/greenfield) into .claude/skills/doc-research in your project. Claude Code loads it when a task matches its description.

How do I install Documentation Research Methodology in Codex?

Run `npx skills add prime-radiant-inc/greenfield --skill doc-research -a codex`. Or copy the skill folder (skills/doc-research in prime-radiant-inc/greenfield) into .agents/skills/doc-research in your project. Codex loads it when a task matches its description.

Can I use Documentation Research Methodology in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add prime-radiant-inc/greenfield --skill doc-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doc-research, .gemini/skills/doc-research, .github/skills/doc-research and .opencode/skills/doc-research in your project.

What does Documentation Research Methodology need to run?

SKILL.md names no scripts, command-line tools or credentials: Documentation Research Methodology is instructions for the agent only. Our summary lists: Web search and page fetching access.

Does Documentation Research Methodology access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Documentation Research Methodology safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Documentation Research Methodology use?

Documentation Research Methodology is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Documentation Research Methodology use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Documentation Research Methodology?

Skills that share tags, products or a category with Documentation Research Methodology: BiSheng SDD Document Review (dataelement/bisheng, 12k stars), Caveman Spec Compression (JuliusBrussee/cavekit, 1.2k stars), Tbd (jlevy/strif, 131 stars) and MVP Technical Design (KhazP/vibe-coding-prompt-template, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Documentation Research Methodology?

prime-radiant-inc (a GitHub organization) maintains it in prime-radiant-inc/greenfield, which has 292 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on August 6, 2026.

Source: prime-radiant-inc/greenfield on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.