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config-codex-cli

Step-by-step agent workflow to configure the OpenAI Codex CLI on any machine (Linux, macOS, Windows) to use OmniRoute as an OpenAI-compatible backend. Detects OS and shell, writes config.toml and 7 named profiles, sets environment variables, and verifies the setup.

44

Quality

45%

Does it follow best practices?

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SecuritybySnyk

Passed

No known issues

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tessl review fix ./skills/config-codex-cli/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

22%

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 thin generated stub that repeats the description and offers only an install snippet, omitting the entire configuration workflow the skill advertises. It is organized into sections but they are placeholders, leaving the content largely non-actionable.

Suggestions

Add the actual step-by-step configuration workflow: OS/shell detection, the config.toml content, the 7 named profiles, environment variable names, and explicit verification commands.

Remove the redundant Overview (it duplicates the frontmatter description) and the empty 'No CLI subcommands mapped' placeholder to tighten token use.

Include an executable example config.toml and profile definitions so the guidance is copy-paste ready rather than descriptive.

DimensionReasoningScore

Conciseness

The body is lean, but the Overview duplicates the frontmatter description verbatim and the 'No CLI subcommands mapped' section is a dead placeholder, so it includes unnecessary content rather than earning every token; not 1 because it does not pad with concepts Claude already knows.

2 / 3

Actionability

Only two install commands are executable; the actual configuration workflow the skill promises (writing config.toml, defining 7 profiles, setting env vars, verifying) is entirely absent, so it describes rather than instructs; not 2 because there is no incomplete-but-present workflow, only a stub.

1 / 3

Workflow Clarity

The skill claims a step-by-step workflow but the body contains no sequenced steps and no validation/verification despite a multi-step configuration task; matches 'steps unclear or missing; no sequence'; not 2 because there is no sequence present at all to evaluate.

1 / 3

Progressive Disclosure

Section headings (Overview, Quick install, Subcommands) provide some structure with no nested references, but the sections are hollow placeholders with no real content to navigate; not 3 because the structure is uninformative stubs rather than well-organized real material.

2 / 3

Total

6

/

12

Passed

Description

67%

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 specific and distinctive with concrete actions and a clear niche, but it lacks an explicit 'Use when...' trigger clause and leans on technical jargon over natural user phrasing, capping completeness and trigger term quality.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger scenarios, e.g. 'Use when the user asks to set up, configure, or switch the Codex CLI to OmniRoute.'

Include more natural phrasings users would say ('set up Codex CLI', 'Codex CLI with OmniRoute') alongside the technical terms to improve trigger term coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Detects OS and shell, writes config.toml and 7 named profiles, sets environment variables, and verifies the setup' — matching the 'lists multiple specific concrete actions' anchor; not below because the actions are specific rather than partial.

3 / 3

Completeness

Clearly answers 'what does this do' with detailed capability list, but provides no 'Use when...' clause or equivalent explicit trigger guidance, so completeness caps at 2 per the rubric guideline.

2 / 3

Trigger Term Quality

Includes product-specific terms a user would say ('OpenAI Codex CLI', 'config.toml') but is dominated by technical jargon ('OpenAI-compatible backend', 'named profiles') and lacks common natural variations; not 3 because coverage of phrasings a user would naturally say is incomplete, not 1 because several genuinely natural keywords appear.

2 / 3

Distinctiveness Conflict Risk

Occupies a clear niche — configuring OpenAI Codex CLI to use OmniRoute as backend — with distinct triggers unlikely to conflict with other skills; not below because the specificity makes misfires improbable.

3 / 3

Total

10

/

12

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
diegosouzapw/OmniRoute
Reviewed

Table of Contents

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