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add-provider

Add a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.

68

Quality

82%

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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.

A well-engineered, repo-specific instruction skill: lean body, concrete file paths, explicit guardrails, a sequenced workflow with validation commands, and a reporting checklist. Remaining improvements are marginal — adding an explicit failure/feedback step after validation and a worked example for the dominant supported path.

Suggestions

Add an explicit feedback loop after step 7: 'If any command or test fails, fix the issue and re-run before reporting' — this closes the workflow_clarity gap from 4 to 5.

Include one short worked example for the OpenAI-compatible path (e.g., the shape of a defaults.ts entry or registry registration) so the most common case is copy-paste ready, strengthening actionability.

Consider a one-line pointer per Supported Path to where its detailed file list lives (or split them into a references/ file) so the three paths read as navigable options rather than inline detail.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence: it contains no concept explanations, no library background, and no padding — every section carries repo-specific facts Claude cannot infer (file paths, auth constraints, validation commands). This matches anchor 5 ('Lean and efficient; every token earns its place'); the only density is the plan.md/tasks.md bookkeeping in workflow step 6, which is information load rather than over-explanation, so it does not drop to anchor 4.

5 / 5

Actionability

Guidance is concrete and mostly executable: exact file paths per path ('src/main/provider/defaults.ts', 'src/main/provider/providerRegistry.ts'), a copy-paste validation block ('pnpm run format / i18n / lint / typecheck'), a required-inputs checklist, and an output checklist. It falls just short of anchor 5 because there is no worked example of the most common case (e.g., a sample registration entry or defaults.ts snippet for the OpenAI-compatible path) — the actual edit shape is left to Claude's inspection of existing files, which is a minor gap rather than the pseudocode-level gap of anchor 3.

4 / 5

Workflow Clarity

The 7-step workflow has a clear sequence with inspection-before-editing, explicit classification, and a validation stage (format, i18n, lint, typecheck, focused tests) plus test-coverage assessment in step 5. It matches anchor 4 ('Clear sequence with most checkpoints present; minor validation gaps') but not anchor 5, because there is no explicit feedback loop stating what to do when a validation command or test fails (fix-and-retry), and the validation gate is not stated as a precondition for reporting results.

4 / 5

Progressive Disclosure

The body is well structured with clear sections (Goal, Required Inputs, three Supported Paths, Guardrails, Workflow, Output Checklist), no nested or buried references, and all in-repo file pointers are concrete. It matches anchor 4 ('Good structure; most content is appropriately placed; minor organization gaps'): with no bundle files provided the skill is self-contained, but the three path sections and their 'Typical files' lists are borderline candidates for split-out reference material, and there is no navigation/signposting beyond the section headers, keeping it below anchor 5's 'well-signaled one-level-deep references'.

4 / 5

Total

17

/

20

Passed

Description

82%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 with an explicit, well-scoped 'Use when...' clause containing concrete repo-specific trigger phrases, and a clear niche that minimizes conflict risk. The main limitation is the capability statement: it names a single action rather than listing several specific actions the skill performs.

DimensionReasoningScore

Specificity

The description names the domain ("DeepChat LLM provider") and one concrete action ("Add a DeepChat LLM provider through explicit reviewed source changes"), but does not enumerate multiple specific actions the skill performs. It clearly matches anchor 3 ("Names domain and 1-2 concrete actions, but not comprehensive") and falls short of anchor 4's "Lists several specific actions", since the enumerated phrases belong to the trigger clause rather than to the capability list.

3 / 5

Completeness

It explicitly answers both questions: 'what' ("Add a DeepChat LLM provider through explicit reviewed source changes") and 'when' ("Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository") with concrete trigger phrases. This matches anchor 5 exactly; anchor 4 would require the 'when' clause to be less explicit or specific, which is not the case.

5 / 5

Trigger Term Quality

The 'Use when' clause covers natural trigger phrasings users would say: "add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter". This is good keyword coverage but not comprehensive — common variations like 'model list', 'API key setup', or 'base URL' (all concepts the body treats as required inputs) are missing, so it sits at anchor 4 rather than anchor 5.

4 / 5

Distinctiveness Conflict Risk

The description carves a clear niche — provider integration in the DeepChat repository — with distinct triggers ('special provider adapter', 'model catalog mapping', 'upstream provider config') unlikely to match unrelated skills. Anchor 5 ("Clear niche with distinct triggers; minimal conflict risk") is the best fit; anchor 4 would require notable overlap with a closely related skill, which is not evident.

5 / 5

Total

17

/

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
ThinkInAIXYZ/deepchat
Reviewed

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