wiki-retro
Skill0 starsChanged 4 months agoMITView on GitHub
Vault retrospective — activity, source mix, topic coverage, health, open questions, and recommendations from logs, git, and wiki-lint.
In this repository36 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- wiki-extract-annasSkill
- wiki-extract-crunchbaseSkill
- wiki-extract-ebookSkill
- wiki-extract-ecommerceSkill
- wiki-extract-githubSkill
- wiki-extract-linkedinSkill
- wiki-extract-newsletterSkill
- wiki-extract-patentsSkill
- wiki-extract-paywallSkill
- wiki-extract-podcastSkill
- wiki-extractSkill
- wiki-extract-wikipediaSkill
- wiki-extract-youtubeSkill
- wiki-fetchSkill
- wiki-ingestSkill
- wiki-learnSkill
- wiki-lintSkill
- wiki-maintainerSkill
- wiki-onboardSkill
- wiki-pipelineSkill
- wiki-querySkill
- wiki-raw-prepareSkill
- wiki-research-academicSkill
- wiki-research-deepSkill
- wiki-research-feedsSkill
- wiki-research-loopSkill
- wiki-research-newsSkill
- wiki-researchSkill
- wiki-research-socialSkill
- wiki-research-webSkill
- wiki-session-memorySkill
- wiki-setupSkill
- wiki-statusSkill
- wiki-upgradeSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 1 is distinctive, and 6 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.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
If git.enabled, use llm-wiki git log / llm-wiki git lifecycle — not the parent repo’s .git for vault operations.
- Very specific: line 20
Read wiki/log.md: count dated sections in the last 7 days (or window in $ARGUMENTS).
- Very specific: line 22
If memory.enabled and raw/memory/ exists, count session files and note recent updated timestamps in frontmatter (wiki-session-memory).
- Very specific: line 27
If raw/.preparation-log.jsonl exists, count prepare / raw finish actions in the window.
- Very specific: line 31
Read wiki/index.md: list sections or topics with most new vs stale pages (use wiki/log.md dates when available).
- Very specific: line 35
Run wiki-lint logic (or invoke the skill): orphans, broken [[wikilinks]], contradictions.
- Distinctive: line 62
If vault git was enabled, commit subjects by phase are referenced when useful.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Wiki retro — Retrospective
Summarize research velocity, source mix, topic coverage, wiki health, and open questions from wiki/log.md, raw/.preparation-log.jsonl (if present), vault git history (if enabled), and a wiki-lint-style pass. Output is read-only analysis plus optional updates to wiki-learn memory.
Pre-flight
- Confirm
llm-wiki/config.jsonexists. Resolve vault root (defaultllm-wiki/). - If
git.enabled, usellm-wiki git log/llm-wiki git lifecycle— not the parent repo’s.gitfor vault operations.
Steps
Step 1 — Activity summary
- Read
wiki/log.md: count dated sections in the last 7 days (or window in$ARGUMENTS). - Note lines matching
research,ingest,pipeline,deep-research, etc. - If
memory.enabledandraw/memory/exists, count session files and note recentupdatedtimestamps in frontmatter (wiki-session-memory).
Step 2 — Source mix
- Scan
raw/**/*.md(sample or full): group bysource_type,platform, or path prefix (raw/news/,raw/academic/, …). - If
raw/.preparation-log.jsonlexists, countprepare/raw finishactions in the window.
Step 3 — Topic coverage
- Read
wiki/index.md: list sections or topics with most new vs stale pages (usewiki/log.mddates when available).
Step 4 — Health
- Run wiki-lint logic (or invoke the skill): orphans, broken
[[wikilinks]], contradictions. - Compare to last retro if
outputs/retro-*.mdexists: delta one-liners.
Step 5 — Open questions
- Aggregate
Open questions:bullets fromwiki/log.mdand lint gaps.
Step 6 — Recommendations
- Propose next research topics, pages to refresh, or integrations to enable.
- Optionally append bullets under
## Next Stepsinllm-wiki/.agent-memory.md(wiki-learn).
Step 7 — Write report
Save to outputs/retro-YYYY-MM-DD.md (create outputs/ if missing):
- Activity summary — sessions, ingests, wiki updates in window
- Source mix — breakdown by type/path
- Topic coverage — hot/cold areas
- Health trend — lint issues; delta vs last retro if known
- Open questions — collected list
- Recommendations — concrete next actions
Done looks like
outputs/retro-YYYY-MM-DD.mdexists with all six sections (use N/A where data is missing).- User gets a short executive summary in chat plus path to the full report.
- If vault git was enabled, commit subjects by phase are referenced when useful.
Artifacts
| Reads | Writes |
wiki/log.md, wiki/index.md, raw/**, raw/memory/**, raw/.preparation-log.jsonl, optional llm-wiki git log | outputs/retro-YYYY-MM-DD.md, optional llm-wiki/.agent-memory.md Next Steps |
Related skills
- wiki-lint — health signals
- wiki-learn — persist recommendations
- wiki-status — tooling/config snapshot
- wiki-pipeline — standard flow for fixes
- wiki-session-memory — per-session
raw/memory/files
Smoke check
- CLI: From the vault root:
llm-wiki validate; if vault git is enabled,llm-wiki git log -n 5. - Prompt: Invoke this skill; confirm retro uses
wiki/log.md/ git history when available.
Optional: persona.name in config (default Gennie).
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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.

