build-evidence-map
Build an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision
Install / Use
npx skills add github/awesome-copilot --skill build-evidence-mapInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Customer SupportSupported Platforms
Our assessment of build-evidence-map
build-evidence-map scores 91/100 on our quality scale, 47th of 188 Customer Support skills we index (top 25%).
Its SKILL.md is 5.0 KB long, split into 4 sections and no code examples: a solid amount of guidance for an agent.
With 39,348 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so build-evidence-map is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
build-evidence-map compared with similar skills
All 4 of these similar skills score higher than build-evidence-map; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| build-evidence-map (this skill)by github | 91 | 39.3k | 3d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 6d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 6d ago | SKILL.md |
Frequently asked questions
- How do I install build-evidence-map?
- Run
npx skills add github/awesome-copilot --skill build-evidence-map. The install tabs above show the steps for each supported agent. - Which AI agents does build-evidence-map work with?
- It is written for GitHub Copilot, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is build-evidence-map safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is build-evidence-map still maintained?
- The repository was last updated 3 days ago, so build-evidence-map is actively maintained.
Skill content
View source on GitHubname: 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
-
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.
-
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.
-
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.
-
Type every edge. Use
supports,contradicts,qualifies, ormissing. 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. -
Preserve counterevidence. Do not delete contrary evidence because the provisional verdict survives it. Represent scope differences with
qualifiesedges. -
Express uncertainty structurally. Do not invent confidence percentages. Add an
unknown, narrow the position, or qualify a claim. -
Write UTF-8 JSON with a
.doubt.jsonsuffix. Follow references/map-schema.md. Keep IDs short, stable, and semantic. -
Validate fail-closed. Resolve
scripts/validate.mjsrelative to thisSKILL.md, then run it with Node.js 18 or newer:node <skill-directory>/scripts/validate.mjs decision.doubt.jsonThe 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
0and printsVALIDfollowed 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:doubt map decision.doubt.json --out decision.html -
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:
doubt verify decision.doubt.json \ --out decision.verified.doubt.jsonNever run this command implicitly. Local file verification does not use the network. Do not write a
verificationobject by hand or hide a mismatch. -
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.
Quality gates
A finished map must satisfy all of these:
- exactly one
positionhas 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
unknownnode; - 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.
Related Skills
algorithmic-art
177.9kCreating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems.
pptx
177.9kUse this skill any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an em…
design
130.2kComprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini, Atlas Cloud, or MuAPI AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social/ads/web/print), icon design (15 styles, SVG…
ui-ux-pro-max
130.2kUI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
