Content
63%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body presents a clear, well-sequenced loop (review → parse → fix → wait → document) with explicit stop conditions, state persistence for recovery, and mostly concrete MCP/curl guidance. Its main costs are duplicated curl and prompt-template blocks, changelog-style meta commentary, and provider/configuration bulk that belongs in a separate reference file — plus shared-reference links that cannot be verified against the bundle.
Suggestions
Deduplicate the curl fallback and reviewer prompt into one parameterized template, and delete the changelog-style note "(Earlier wording used `or` and a stale verdict set; the `AND` form is authoritative.)" in favor of the single authoritative statement.
Move the 9-provider configuration table and MCP settings example into a references/ file (e.g. references/providers.md) and link to it, keeping SKILL.md as a lean overview.
Add explicit error-handling checkpoints: what to do when the review response has no parseable score, when the MCP call or curl fails, and how many retries before aborting — this would also lift workflow clarity toward anchor 5.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Quotes: the curl fallback appears three times ("## API Call Method", "#### Phase A" fallback, and again verbatim), the reviewer prompt template is repeated (Phase A and "## Prompt Template for Round 2+"), and changelog-style meta commentary is inlined ("(Earlier wording used `or` and a stale verdict set; the `AND` form is authoritative.)"). The content is mostly efficient and free of concept over-explanation, but the duplication and self-referential notes mean it could be tightened, matching anchor 3 ("mostly efficient but includes some unnecessary explanation or could be tightened"). | 3 / 5 |
Actionability | Quotes: concrete MCP invocations ("mcp__llm-chat__chat:" with prompt/model/system fields), a copy-paste curl command with the full JSON body ("curl -s "${LLM_BASE_URL}/chat/completions" ... -d '{"model": "${LLM_MODEL}", "messages": [...], "max_tokens": 4096}'"), an exact state-file schema, and a complete output markdown template. Placeholders like "[Full research context: claims, methods, results, known weaknesses]" are appropriate parameterization for a loop skill, leaving only minor gaps (e.g. no jq/python snippet for parsing the score out of the response), fitting anchor 4 ("mostly executable guidance; concrete code or commands with minor gaps"). | 4 / 5 |
Workflow Clarity | Quotes: "### Initialization ... 1. Check `review-stage/REVIEW_STATE.json` for recovery", "### Loop (up to MAX_ROUNDS)" with Phases A-E, an explicit STOP checkpoint ("**STOP**: If score >= 6 AND verdict ∈ {"ready", "almost"}"), and termination steps ("Set `review-stage/REVIEW_STATE.json` status to "completed""). The entire skill is a validate→fix→retry feedback loop with state recovery, matching anchor 4; it falls short of 5 only because there is no error-recovery checkpoint for API failures or unparseable review responses. | 4 / 5 |
Progressive Disclosure | The body links four one-level-deep shared references ("[Output Versioning Protocol](../shared-references/output-versioning.md)", output-manifest, output-language, and external-cadence), but no references/, scripts/, or assets/ bundle files exist and the ../shared-references/*.md targets are not present in the bundle, so the links cannot be verified. Meanwhile substantial configuration bulk (a 9-provider table of base URLs and models, full curl bodies) is inlined in SKILL.md rather than split out, fitting anchor 3 ("some structure but could be better organized; ... content that should be separate is inline"). | 3 / 5 |
Total | 14 / 20 Passed |