wiki-qa
Skill4 starsChanged 4 months agoMITView on GitHub
Answer a teammate's free-form lookup question about this project's planning/wiki content (e.g. "what billing model did we settle on yesterday?", "how does X stand?", "how are Y and Z related?", "what's the payment scope?") by querying the graphify graph to narrow to the relevant concepts and reading only those source files (token-efficient and scales as the wiki grows), answering with cited evidence and surfacing graph-connected concepts — pure read-only Q&A; explicit work like conflict detection, refining, sprint, or backlog belongs to those skills.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- microsoft/skillstheir own version, first seen Oct 13, 2026
- microsoft/agent-skillstheir own version, first seen Oct 8, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- microsoft/agent-skills★ 3.2ksame name
- microsoft/skills★ 3.2ksame name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- backlog-proposalSkill
- backlog-updateSkill
- conflict-detectionSkill
- daily-scrumSkill
- impact-analysisSkill
- loremaster-setupSkill
- meeting-agendaSkill
- refine-wikiSkill
- resolve-conflictsSkill
- sprint-planningSkill
- sprint-retroSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 66
If the question is a change request rather than a lookup (planning edit, decision, backlog): do not answer it — hand off to the relevant …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Wiki Q&A — graphify graph-based retrieval
Answer the team's wiki/planning questions without guessing, grounded in the actual documents. The key is to not read everything: use the graphify graph first to narrow down "where to read" — token-efficient, and scales as the wiki grows.
Principles (invariant)
- No answer without evidence. Quote only what actually exists in raw/wiki. No guessing, no invention — if it isn't there, answer "not there yet / undecided".
- Cite sources. State which files the answer came from
(e.g.
(sources: wiki/concepts/billing-model.md, raw/PRD.md)). - This channel = this project's lore vault only. Never pull in concepts from other projects.
related/[[ ]]are graphify-derived views — never edit them directly (read only).
Retrieval procedure
Working directory is the project lore vault root (where graphify-out/, wiki/,
raw/ are visible).
- Narrow the concepts — query graphify first:
- Free-form query:
graphify query "<keyword>" --graph graphify-out/graph.json→ returns the start node plus a BFS-connected subgraph of related nodes, edges, and source file paths. Query with the question's key concept term as it is worded in the wiki (e.g. "billing model", "payment scope"). - Detail on one concept:
graphify explain "<concept>"→ that node's neighbors and relations (depends_on/references etc.). - Relation/ripple between two concepts:
graphify path "<A>" "<B>"→ shortest path. - If nothing matches (label mismatch, synonym, typo): look up the related
concept name in
wiki/index.md(the concept catalog, one-line summaries) and re-query with that name, or fall back tosearch_files(grep). Never force a guessed answer.
- Free-form query:
- Read the evidence (only what was narrowed):
read_fileonly thewiki/concepts/<concept>.mdfiles that query/explain pointed to. If decision history or original wording is needed, also the relevant parts ofraw/PRD.mdandraw/decisions/*.md. Do not read whole files the graph did not point to. - Answer: answer concisely from what you read and attach the sources. Add
one line of graph-connected concepts (e.g.
Related: payment scope, free-plan policy) — surfacing connections even when unasked is graphify's value.
Fallbacks / limits
- If graph.json is missing (not yet built): answer via
wiki/index.md+ directread_file, and if the wiki looks like it needs refinement, point to refine-wiki. graphify querymatches on node names, so it is weak on synonyms and spelling → on a miss, fall back to index.md/search_files; if still nothing, honestly answer "no evidence in the wiki".- If the question is a change request rather than a lookup (planning edit, decision, backlog): do not answer it — hand off to the relevant skill (resolve-conflicts/backlog-update etc.) and its approval gate. Q&A is read-only.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.