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consult-zai

Dual-AI code analysis pairing z.ai GLM 5.2 with Claude code-searcher — a lightweight two-model second opinion. Use for a quick z.ai-backed check on a code question.

58

Quality

73%

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SecuritybySnyk

Low

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tessl review fix ./.claude/skills/consult-zai/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%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.

An operationally rigorous skill with exceptional workflow validation and near-copy-paste actionability, covering failure modes most skills ignore. Its weaknesses are verbosity (dated field notes and inline rationale in the dispatch path) and zero progressive disclosure — the whole operational manual lives in SKILL.md with no reference files.

Suggestions

Move the 'Why this exact form' flag rationale, the timeout-watchdog notes, and the §5 comparison template into a references/ file (e.g., references/dispatch-notes.md), keeping SKILL.md as a lean overview with clearly signaled one-level-deep pointers.

Give an executable RUN_ID command (e.g., RUN_ID="run-$(date +%Y-%m-%d-%H%M%S)-$(openssl rand -hex 2)") instead of describing the format, making the dispatch fully copy-paste ready.

Trim time-stamped asides ('verified 2026-07-18', 'reported live 2026-08-01') and the cross-reference to 'consult-panel §1d' from the main workflow; if the dates matter, put them in a notes/reference section so the main path stays lean.

DimensionReasoningScore

Conciseness

Most of the dense operational detail (tool-flag gotchas, dispatch race guard, timeout rationale) is non-obvious knowledge that earns its tokens, but there is noticeable padding: the multi-bullet "Why this exact form" rationale, time-stamped notes ("verified 2026-07-18", "reported live 2026-08-01"), and cross-references to an external skill ("consult-panel §1d"). Not a 2 because little of the content explains things Claude already knows; not a 4 because the rationale commentary and dated asides could be substantially trimmed or moved out of the main flow.

3 / 5

Actionability

The skill provides copy-paste-ready bash for setup, dispatch, jq parsing (with a bare-object fallback), and cleanup, plus an exact output template. Minor gaps keep it from a 5: RUN_ID generation is described ("seconds-resolution + 4-char nonce") but never given as an executable command, and the z.ai prompt-file Write step is a prose instruction rather than a concrete tool call.

4 / 5

Workflow Clarity

The §1-§5 sequence is explicit with strong validation checkpoints and recovery loops: fail-fast pre-flight (PROJECT_DIR directory check before mkdir, jq hard-dependency abort, zai availability probe with shell capture), a timeout watchdog with exit-code handling (124 = SIGTERM, 137 = SIGKILL) and a no-retry rule, a parse guard with fallback recipe, and §4 error handling that quotes stderr before cleanup and labels degraded single-AI runs. This matches the anchor for clear sequence with explicit validation and error-recovery feedback loops.

5 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/), so everything — flag rationale, timeout watchdog notes, jq recipe, comparison template — is inlined in a ~300-line single file. Section headers and numbered steps give it real structure, but content that clearly belongs in separate reference files is inline, and the one pointer ("consult-panel §1d") targets something outside this bundle. Not a 2 because the structure is well-organized and navigable, not minimal.

3 / 5

Total

15

/

20

Passed

Description

62%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 concise, distinctive description that clearly states both what the skill does and when to use it. Its weaknesses are thin action coverage and generic trigger phrasing — "a quick z.ai-backed check on a code question" could name the concrete query types (debugging, architecture, review) the body targets.

Suggestions

Enumerate 2-3 concrete capabilities (e.g., 'runs both models on a code question and synthesizes a corroborated comparison report with file:line citations') to lift specificity.

Replace the generic 'a code question' trigger with concrete phrases users would actually say, e.g. 'Use when the user wants a second opinion on a bug, an architecture question, or a code review cross-checked by another model.'

Include natural synonyms such as 'second opinion', 'cross-check', or 'dual-AI review' so the description matches how users phrase the request.

DimensionReasoningScore

Specificity

"Dual-AI code analysis pairing z.ai GLM 5.2 with Claude code-searcher" names the domain plus a concrete capability (a two-model "second opinion"), but only sketches 1-2 actions without covering what the skill actually does (comparison reports, citation corroboration, degraded-run handling). It is not a 4 because it does not list several specific actions with only minor gaps.

3 / 5

Completeness

The description explicitly answers both: what ("Dual-AI code analysis pairing z.ai GLM 5.2 with Claude code-searcher — a lightweight two-model second opinion") and when ("Use for a quick z.ai-backed check on a code question"). Not a 5 because the trigger clause is generic ("a code question") rather than concrete trigger phrases.

4 / 5

Trigger Term Quality

"code analysis", "second opinion", and "check on a code question" are natural phrases, but common user variants like "second-opinion on this bug", "cross-check", "another AI's take", or "review this code" are missing. Not a 4 because keyword coverage is thin rather than good-with-a-few-gaps.

3 / 5

Distinctiveness Conflict Risk

The z.ai GLM 5.2 / code-searcher dual-model framing carves a clear niche unlikely to fire for unrelated skills, though "code analysis" broadly overlaps generic code-review skills. Not a 5 because that residual overlap with review/analysis skills remains.

4 / 5

Total

14

/

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
centminmod/my-claude-code-setup
Reviewed

Table of Contents

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