New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Official agent skill

Evidence Map Builder

by github in github/awesome-copilot

Turns one contested decision into a validated JSON map of supporting, contradicting, qualifying and missing evidence, with exact source locations.

OfficialMITAuto-check passedResearch & Science

Install Evidence Map Builder

skills CLI
$ npx skills add github/awesome-copilot --skill build-evidence-map -a claude-code

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

GitHub CLI
$ gh skill install github/awesome-copilot build-evidence-map --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/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/build-evidence-map .claude/skills/build-evidence-map && 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
build-evidence-map
GitHub stars
40k
Token cost
~1.3k tokens
SKILL.md length
616 words
Files
5 (incl. scripts, references)
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

Turns one contested decision into a validated JSON map of supporting, contradicting, qualifying and missing evidence, with exact source locations.

  • Works in 10 steps: Frame one decision. Write one… → Collect bounded source regions. Prefer… → Atomize the reasoning. Create only four… → …
  • Comparing two technical options when sources disagree
  • SKILL.md covers Workflow, Quality gates and Deliver the result
  • Runs JavaScript scripts from its folder; calls node

What it does

The agent frames a single falsifiable question with a provisional position, then collects bounded source regions, preferring primary sources and recording the URL or absolute path, publisher, publication and retrieval dates, a locator such as page or line, and a short checkable excerpt. The reasoning is broken into four node types: position, claim, evidence and unknown. Every link is typed as supports, contradicts, qualifies or missing, with a plain-language note, and contrary evidence stays in the map instead of being discarded.

Uncertainty is shown structurally, by adding an unknown or narrowing a claim, and invented confidence percentages are ruled out. The map is written as UTF-8 JSON with a `.doubt.json` suffix following `references/map-schema.md`, then checked with the bundled `scripts/validate.mjs`, which needs Node.js 18 or newer, uses only built-ins and fails closed until every finding is fixed. For simple factual claims the skill points to a verification workflow instead.

When your agent uses it

  • Comparing two technical options when sources disagree
  • Reviewing a proposal while preserving the evidence for and against it
  • Recording a consequential decision in a form others can audit

Example prompts

  • “Build an evidence map on whether we should move our queue from RabbitMQ to Kafka.”
  • “Map the sources for and against adopting this vendor's pricing proposal and flag what is still unknown.”
  • “Validate decision.doubt.json and fix every finding before reporting.”

Requirements

  • Node.js 18 or newer for the bundled validator

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Frame one decision. Write one falsifiable question and one provisional
  2. Collect bounded source regions. Prefer direct observations and primary
  3. Atomize the reasoning. Create only four node types
  4. Type every edge. Use supports, contradicts, qualifies, or
  5. Preserve counterevidence. Do not delete contrary evidence because the
  6. Express uncertainty structurally. Do not invent confidence percentages.
  7. Write UTF-8 JSON with a .doubt.json suffix. Follow
  8. Validate fail-closed. Resolve
  9. Verify source snapshots only with explicit network permission. The
  10. Inspect the deliverable. Confirm that the question, verdict,

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. 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

    Ships 2 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • node

    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

Evidence Map Builder loads about 1.3k tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 616 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.5k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 616 words, ~1,270 tokens.

Download SKILL.mdSave it as .claude/skills/build-evidence-map/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
build-evidence-map
description
Build an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision. Use when Copilot must preserve supporting, contradicting, qualifying, and missing evidence with exact source regions instead of collapsing disagreement into prose.

Build Evidence Map

Turn one contested question into a portable decision artifact that shows what supports the current position, what pushes against it, and what remains unknown. Do not use a graph to decorate an answer that has not been sourced.

For a simple factual claim or a general fact-checking request, use a verification workflow such as doublecheck instead. Use this skill when the relationships between evidence, intermediate claims, trade-offs, and missing facts matter.

Workflow

  1. Frame one decision. Write one falsifiable question and one provisional position. Narrow the question until a reader can identify what action or belief the map is testing.

  2. Collect bounded source regions. Prefer direct observations and primary sources. Record the URL or absolute local path, publisher, publication date, retrieval date, section/page/line/timestamp locator, and a short checkable excerpt. Read references/evidence-ladder.md when source quality is disputed.

  3. Atomize the reasoning. Create only four node types:

    • position: the single current verdict;
    • claim: an intermediate proposition;
    • evidence: a faithful statement of one source region;
    • unknown: a specific missing fact that could change the verdict.

  4. Type every edge. Use supports, contradicts, qualifies, or missing. Add a plain-language note explaining why the source node bears on the target. Topical similarity is not support. Different scope, date, or population is not automatically a contradiction.

  5. Preserve counterevidence. Do not delete contrary evidence because the provisional verdict survives it. Represent scope differences with qualifies edges.

  6. Express uncertainty structurally. Do not invent confidence percentages. Add an unknown, narrow the position, or qualify a claim.

  7. Write UTF-8 JSON with a .doubt.json suffix. Follow references/map-schema.md. Keep IDs short, stable, and semantic.

  8. Validate fail-closed. Resolve scripts/validate.mjs relative to this SKILL.md, then run it with Node.js 18 or newer:

    bash
    node <skill-directory>/scripts/validate.mjs decision.doubt.json

    The bundled validator uses only Node.js built-ins and does not require npm or network access. Fix every finding before reporting success. Only say the map is valid when the command exits 0 and prints VALID followed by a 64-character receipt. A file hash, node count, JSON parse, or manual schema review is not a Doubt receipt. If deterministic validation cannot run, report that block instead of inventing success.

    Render the validated map only when the user has already installed doubt-ai@0.8.0; do not install or execute a remote package implicitly:

    bash
    doubt map decision.doubt.json --out decision.html

  9. Verify source snapshots only with explicit network permission. The following command retrieves each recorded HTTP(S) source and fails closed if an excerpt cannot be matched:

    bash
    doubt verify decision.doubt.json \
  --out decision.verified.doubt.json

    Never run this command implicitly. Local file verification does not use the network. Do not write a verification object by hand or hide a mismatch.

  10. Inspect the deliverable. Confirm that the question, verdict, counterevidence, unknowns, edge notes, and exact source regions remain readable. Treat JSON as the canonical editable artifact; HTML is a shareable view.

Show full SKILL.md (159 more words)Show less

Quality gates

A finished map must satisfy all of these:

  • exactly one position has incoming reasoning;
  • every evidence node names one source and participates in an edge;
  • every source is used and has dates, a bounded locator, and a substantive excerpt;
  • every non-position node has a directed path to the position;
  • the reasoning graph has no duplicate edges or directed cycles;
  • contrary or qualifying evidence is present when the source set contains it;
  • each decision-changing gap is an explicit unknown node;
  • every edge note explains support, contradiction, qualification, or absence;
  • the verdict is no broader than the evidence.

Deliver the result

Report:

  • the current position in one sentence;
  • the strongest counterevidence or qualification;
  • the most important unresolved unknown;
  • paths to the canonical JSON and any rendered HTML;
  • whether deterministic validation and explicit source verification ran.

Never describe a structurally valid map as proven true. Validation establishes traceability and graph integrity; source quality and inference quality still require human review.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/build-evidence-map of github/awesome-copilot.

  • SKILL.md
  • references/evidence-ladder.md
  • references/map-schema.md
  • scripts/contract.mjs
  • scripts/validate.mjs

Open the folder on GitHubat commit 727ff2e

Compare with similar skills

Evidence Map Builder next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Evidence Map Builder compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Evidence Map Builder this skillgithub/awesome-copilot40k—~1.3kAutomated safety check: PassMIT
Perplexity Web Searchdavila7/claude-code-templates32k12 repos~3.5kAutomated safety check: NotesMIT
Citation Verification GuideGalaxy-Dawn/claude-scholar5.7k3 repos~1.9kAutomated safety check: PassMIT
Article Fact Checkerdigoal/blog8.6k—~939Automated safety check: PassGPL-2.0
Deep Research Agent TeamImbad0202/academic-research-skills51k—~13kAutomated safety check: PassCustom licence
Docs Grounding Verifiermicrosoft/apm4k—~1.9kAutomated safety check: PassMIT

Similar skills

  • Perplexity Web Search

    davila7/claude-code-templates

    Runs web-grounded searches through Perplexity's Sonar models over OpenRouter for current events, recent literature and cited facts beyond the model's training cutoff.

    32k GitHub starsUsed in 12 repos~3.5k tokens
    Research & ScienceAuto-check: notes

  • Citation Verification Guide

    Galaxy-Dawn/claude-scholar

    Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references.

    5.7k GitHub starsUsed in 3 repos~1.9k tokens
    Research & ScienceAuto-check passed

  • Article Fact Checker

    digoal/blog

    三层审查模型,逐段逐句验证文章真伪、证据链与逻辑结构。Use when the user asks to fact-check, verify, audit, or evaluate the credibility of an article, essay, report, opinion piece, social-media post, or any written claim —…

    8.6k GitHub stars~939 tokensUpdated 9 days ago
    Research & ScienceAuto-check passed

  • Deep Research Agent Team

    Imbad0202/academic-research-skills

    Runs a 13-agent pipeline for rigorous academic research, from forming the question through systematic search, synthesis, bias checks and an APA 7.0 report.

    51k GitHub stars~13k tokensUpdated 4 days ago
    Research & ScienceAuto-check passed

  • Docs Grounding Verifier

    microsoft/apm

    Official

    A skill your agent uses to verify CLAIM-LEVEL grounding of a documentation page (or set of pages) against the source code.

    4k GitHub stars~1.9k tokensUpdated yesterday
    Research & ScienceAuto-check passed

  • Fact Checking

    bradygaster/squad

    Review and validate claims using counter-hypothesis testing.

    3.3k GitHub stars~503 tokensUpdated yesterday
    Research & ScienceAuto-check passed

More from github/awesome-copilot

All 417 skills in this repo

  • Acquire Codebase Knowledge

    github/awesome-copilot

    Official

    Maps an unfamiliar codebase into seven evidence-backed documents in docs/codebase/, using a scan script and templates, for onboarding or architecture write-ups.

    40k GitHub starsUsed in 1 repo~2.3k tokens
    Auto-check passed

  • Azure Architecture Autopilot

    github/awesome-copilot

    Official

    Designs Azure infrastructure from a natural-language description, or diagrams an existing resource group, then refines the design through conversation and deploys it with Bicep.

    40k GitHub starsUsed in 1 repo~1.9k tokens
    Auto-check passed

  • Draw.io Diagram Generator

    github/awesome-copilot

    Official

    Generates, edits and validates draw.io files with correct mxGraph XML, covering flowcharts, architecture, sequence, ER and UML class diagrams.

    40k GitHub starsUsed in 1 repo~4.9k tokens
    Auto-check passed

  • Credit Risk Data Cleaning

    github/awesome-copilot

    Official

    Cleans raw credit data and screens variables before loan modeling, dropping unstable, noisy or redundant features and writing an Excel report of every step.

    40k GitHub starsUsed in 1 repo~1.5k tokens
    Auto-check passed

  • Daily Focus Board

    github/awesome-copilot

    Official

    Builds a warm, browser-based daily focus board the user updates by talking to their agent, with Eisenhower priorities, a brain-dump box and kind not-today carryover.

    40k GitHub stars~3k tokensUpdated today
    Auto-check passed

  • Python Pypi Package Builder

    github/awesome-copilot

    Official

    End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI.

    40k GitHub starsUsed in 1 repo~4.6k tokens
    Auto-check passed

Categories

Questions about Evidence Map Builder

What does Evidence Map Builder do?

Turns one contested decision into a validated JSON map of supporting, contradicting, qualifying and missing evidence, with exact source locations. The agent frames a single falsifiable question with a provisional position, then collects bounded source regions, preferring primary sources and recording the URL or absolute path, publisher, publication and retrieval dates, a locator such as page or line, and a short checkable excerpt. The reasoning is broken into four node types: position, claim, evidence and unknown.

When should I use Evidence Map Builder?

Evidence Map Builder fits situations like: comparing two technical options when sources disagree; reviewing a proposal while preserving the evidence for and against it; recording a consequential decision in a form others can audit.

How do I install Evidence Map Builder in Claude Code?

Run `npx skills add github/awesome-copilot --skill build-evidence-map -a claude-code`. Or copy the skill folder (skills/build-evidence-map in github/awesome-copilot) into .claude/skills/build-evidence-map in your project. Claude Code loads it when a task matches its description.

How do I install Evidence Map Builder in Codex?

Run `npx skills add github/awesome-copilot --skill build-evidence-map -a codex`. Or copy the skill folder (skills/build-evidence-map in github/awesome-copilot) into .agents/skills/build-evidence-map in your project. Codex loads it when a task matches its description.

Can I use Evidence Map Builder 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 github/awesome-copilot --skill build-evidence-map -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/build-evidence-map, .gemini/skills/build-evidence-map, .github/skills/build-evidence-map and .opencode/skills/build-evidence-map in your project.

What does Evidence Map Builder need to run?

Going by SKILL.md and its folder, Evidence Map Builder needs JavaScript for the scripts in its folder and the command-line tools its instructions call (node). Our summary lists: Node.js 18 or newer for the bundled validator.

Does Evidence Map Builder 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 Evidence Map Builder 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Evidence Map Builder use?

Evidence Map Builder is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Evidence Map Builder use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.3k tokens, read only when the agent opens those files.

What are the alternatives to Evidence Map Builder?

Skills that share tags, products or a category with Evidence Map Builder: Perplexity Web Search (davila7/claude-code-templates, 32k stars), Citation Verification Guide (Galaxy-Dawn/claude-scholar, 5.7k stars), Article Fact Checker (digoal/blog, 8.6k stars) and Deep Research Agent Team (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Evidence Map Builder?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.