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wiki-agent

Search one AI agent's raw history for a specific topic, ingest only matching sessions, and return a synthesized answer. Use for targeted cross-agent recall; use wiki-history-ingest for bulk archival ingestion.

Quality

88%

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SKILL.md
Quality
Evals
Security

Quality

Content

77%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.

A highly actionable, well-sequenced operational skill: every step carries exact paths, commands, templates, and error-recovery guidance, with validation and lock discipline for the batch writes. Its weaknesses are the monolithic inlining of six per-agent reference sections (no bundle files at all), the partially redundant Cross-Agent Use Patterns section, and a vague Copilot section.

Suggestions

Split the per-agent sections of Steps 2 and 4 into references/<agent>.md files (e.g. references/claude.md, references/codex.md) so only the invoked agent's inventory and extraction details load into context, keeping SKILL.md to the shared workflow and routing.

Trim or collapse the Cross-Agent Use Patterns section to the one genuinely new pattern (running /wiki-<agent> for several agents in sequence, then /memory-bridge diff); the no-query and single-agent examples restate the routing table and the recent-sessions default.

Firm up the Copilot section: commit to the concrete VS Code path and index format, or state the discovery procedure (find session files by mtime/pattern) instead of 'or similar'.

DimensionReasoningScore

Conciseness

The body is dense with operational specifics (paths, index fields, scoring formula, exact commands) and explains nothing Claude already knows, but the ~25-line "Cross-Agent Use Patterns" section largely restates the routing table and the no-query default already stated above (e.g. "catch me up on recent Codex work" → /wiki-codex repeats the recent-sessions default). Efficient with minor trimmable redundancy — anchor 4, not the every-token-earns-its-place of a 5.

4 / 5

Actionability

Mostly copy-paste-ready: exact `rg -i` extraction commands, a concrete decay formula, a complete frontmatter template, an exact answer template, and exact `obsidian-wiki memory sync` and `qmd` invocations. Held below 5 because the Copilot section hedges ("varies by client (VS Code: ~/.copilot/sessions/*.jsonl or similar)") rather than being fully executable, matching 'concrete code or commands with minor gaps'.

4 / 5

Workflow Clarity

Seven explicitly sequenced steps with validation and error recovery at each fragile point: missing history root → stop with an exact user message; no matching sessions → exact no-results message; QMD failure → "do not roll back the vault changes; report the QMD status separately"; lock discipline → "Never hand-edit index.md, log.md, or hot.md". The batch ingest also has checkpoints (manifest check, existing-page check, qmd verification), matching the feedback-loop-rich top anchor.

5 / 5

Progressive Disclosure

No bundle files exist; the ~320-line body inlines per-agent inventory and extraction details for all six agents (Steps 2 and 4) that would ideally live in per-agent reference files so only the target agent's detail loads. External delegation (llm-wiki/SKILL.md, .skills/llm-wiki/references/MEMORY.md) is clearly signaled and one level deep, and sections are well-organized — better than anchor 2, but the inline per-agent reference material fits anchor 3 ('content that should be separate is inline') better than anchor 4.

3 / 5

Total

16

/

20

Passed

Description

92%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.

A strong description: it names the full workflow in concrete verbs, gives an explicit use clause, and explicitly routes bulk ingestion to the sibling skill. The only weakness is that its trigger vocabulary is skill-ecosystem jargon ("cross-agent recall") rather than the phrases a user would naturally type.

DimensionReasoningScore

Specificity

"Search one AI agent's raw history for a specific topic, ingest only matching sessions, and return a synthesized answer" lists three concrete actions covering the full pipeline (find → ingest → answer). Not 4, because coverage is comprehensive rather than having minor gaps.

5 / 5

Completeness

The 'what' is answered with three concrete actions and the 'when' is explicit via "Use for targeted cross-agent recall", plus a boundary ("use wiki-history-ingest for bulk archival ingestion"). Both are clearly and explicitly answered with concrete trigger guidance, matching the top anchor rather than the 'when could be more explicit' of a 4.

5 / 5

Trigger Term Quality

Relevant keywords are present ("raw history", "specific topic", "matching sessions", "cross-agent recall") but natural user phrasings like "past conversations", "chat history", or "what did I figure out about X" are missing. Fits 'good keyword coverage; a few natural terms missing', not the comprehensive synonym/extension coverage of a 5.

4 / 5

Distinctiveness Conflict Risk

"Use for targeted cross-agent recall; use wiki-history-ingest for bulk archival ingestion" carves out a clear niche and explicitly disambiguates from the nearest sibling skill. Minimal conflict risk.

5 / 5

Total

19

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Ar9av/obsidian-wiki

Path

.skills/wiki-agent/SKILL.md

Reviewed

Table of Contents

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