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wiki-agent

Query-driven targeted ingest from a specific AI agent's raw history. Use this skill when the user invokes /wiki-claude, /wiki-codex, /wiki-hermes, /wiki-openclaw, /wiki-copilot, /wiki-pi — with or without a search topic. Different from wiki-history-ingest (which bulk-ingests everything new): this skill finds sessions about a SPECIFIC TOPIC in a specific agent's history and ingests just those, then returns a synthesized answer immediately usable in the current session. Primary use case: you're working in agent A and want to pull in how you solved X in agent B's history. Cross-referencing, not archiving. Also trigger on: "what did I work on in codex about X", "search my claude sessions for Y", "pull in hermes knowledge about Z", "find that conversation where I did X in codex".

74

Quality

91%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a thorough, highly actionable multi-agent ingest workflow with concrete paths, commands, formulas, and templates, and it includes real validation checkpoints. It loses points only for some redundancy in the Cross-Agent section and the absence of an explicit post-write validation feedback loop.

Suggestions

Trim the 'Cross-Agent Use Patterns' section or fold it into the Command Routing table, since much of it restates commands already shown.

Add an explicit post-write validation step (e.g., re-grep index.md / open the updated page to confirm the new content rendered) with a fix-and-retry loop for the batch wiki-write in Step 5.

Consider moving the per-agent extraction strategies (Step 4) into a reference file indexed by agent, keeping SKILL.md as a routing overview.

DimensionReasoningScore

Conciseness

The body is mostly lean and assumes competence (exact paths, signal fields, a decay formula rather than explaining JSONL), but the 'Cross-Agent Use Patterns' section partly rehashes the Command Routing table and the 'this is not bulk ingest' framing is stated more than once.

4 / 5

Actionability

Fully executable guidance throughout: exact history paths per agent, exact signal fields, `rg -i` extraction commands, a concrete scoring formula in code, required frontmatter templates, and copy-paste qmd commands — covering the common cases ready to run.

5 / 5

Workflow Clarity

Seven clearly sequenced steps with prep and checkpoints (history-root existence guard, manifest already-ingested check, existing-page check before creating, QMD verification), but there is no explicit validate-then-fix feedback loop after writing wiki pages, leaving a minor validation gap in this batch-write workflow.

4 / 5

Progressive Disclosure

Well-organized into clearly headed sections with one-level-deep, clearly signaled references to llm-wiki/SKILL.md and vault files; no bundle files exist, and the per-agent extraction detail is inlined rather than split into reference files, which is reasonable but keeps the body fairly monolithic.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: it states concrete capabilities, provides both command and natural-language triggers, answers what and when explicitly, and sharply differentiates itself from a sibling skill. The only minor voice nit ('you're working in agent A') is scenario description rather than the penalized 'You can use this' phrasing, so it does not warrant a reduction.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Query-driven targeted ingest', 'finds sessions about a SPECIFIC TOPIC', 'ingests just those', 'returns a synthesized answer' — giving comprehensive coverage of what the skill does.

5 / 5

Completeness

Explicitly answers both 'what' (targeted ingest of topic-matched sessions from one agent's history, returning a synthesized answer) and 'when' ('Use this skill when the user invokes /wiki-...' plus concrete trigger phrases), satisfying the strongest anchor.

5 / 5

Trigger Term Quality

Combines explicit command triggers (/wiki-claude, /wiki-codex, etc.) with natural user phrases like 'what did I work on in codex about X' and 'find that conversation where I did X in codex', covering synonyms and phrasings users actually say.

5 / 5

Distinctiveness Conflict Risk

Carves a clear niche (specific-agent + specific-topic query ingest) and explicitly distinguishes itself from wiki-history-ingest ('Different from wiki-history-ingest which bulk-ingests everything new'), minimizing wrong-skill triggering.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Ar9av/obsidian-wiki
Reviewed

Table of Contents

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