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issue-discover

Unified issue discovery and creation. Create issues from GitHub/text, discover issues via multi-perspective analysis, or prompt-driven iterative exploration. Triggers on "issue:new", "issue:discover", "issue:discover-by-prompt", "create issue", "discover issues", "find issues".

58

Quality

67%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Fix and improve this skill with Tessl

tessl review fix ./.codex/skills/issue-discover/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

35%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is significantly over-engineered for a routing/orchestration document. It contains extensive pseudocode, architecture diagrams, and API references that bloat the context window without proportional value — much of this could be inferred by Claude or moved to reference files. The core routing logic and phase references are sound, but the skill tries to be both a high-level orchestrator and a detailed implementation guide, succeeding at neither optimally.

Suggestions

Reduce content by 60%+: Remove the ASCII architecture diagram, auto-detection JavaScript pseudocode, and detailed subagent API reference — move these to a separate reference file if needed. The SKILL.md should focus on routing rules and phase references.

Move the subagent API reference (spawn_agent, wait_agent, followup_task, close_agent) to a separate SUBAGENT-API.md file and reference it, as this is reusable knowledge not specific to issue discovery.

Add explicit validation steps: after loading a phase document, verify it loaded successfully; after phase execution, validate outputs before proceeding to post-phase steps.

Consolidate the request_user_input examples into a single compact pattern rather than showing full JavaScript blocks for each decision point — Claude can generalize from one example.

DimensionReasoningScore

Conciseness

Extremely verbose at ~300+ lines. Contains extensive architecture diagrams, JavaScript pseudocode for auto-detection logic, detailed subagent API reference, and request_user_input examples that Claude doesn't need spelled out in such detail. The ASCII art architecture diagram, data flow diagrams, and repeated explanations of routing logic are redundant. Much of this content (subagent API, CLI reference) should be in separate files or omitted entirely.

1 / 3

Actionability

Provides concrete code examples for action selection, auto-detection logic, and subagent API calls, but these are pseudocode/illustrative rather than truly executable. The CLI examples in the Usage section are helpful and specific. However, the actual phase execution logic is deferred to phase documents that aren't provided, making the skill itself more of a routing description than actionable guidance.

2 / 3

Workflow Clarity

The execution flow is clearly sequenced with input parsing → action selection → phase execution → post-phase steps. However, validation checkpoints are largely missing — there's no explicit verification that phase documents loaded correctly, no validation of input parsing results, and error handling is a simple table without feedback loops. The 'Phase execution fails → suggest manual intervention' is vague.

2 / 3

Progressive Disclosure

References to phase documents (phases/01-04) are well-structured in a table with clear load conditions. However, the SKILL.md itself is a monolithic wall of content that should have much of its detail (subagent API reference, auto-detection pseudocode, detailed request_user_input examples) moved to separate reference files. The bundle has no files provided, so we can't verify the phase references exist.

2 / 3

Total

7

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong skill description that concisely covers what the skill does (issue creation and discovery through multiple methods) and when to use it (with explicit trigger terms). It uses third person voice appropriately and provides enough specificity to distinguish it from other skills. The only minor weakness is that 'multi-perspective analysis' is slightly jargon-heavy, but the natural language triggers compensate well.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: creating issues from GitHub/text, discovering issues via multi-perspective analysis, and prompt-driven iterative exploration. These are distinct, concrete capabilities.

3 / 3

Completeness

Clearly answers 'what' (create issues from GitHub/text, discover issues via multi-perspective analysis, prompt-driven exploration) and 'when' with explicit trigger terms listed after 'Triggers on'. The trigger guidance is explicit.

3 / 3

Trigger Term Quality

Includes both natural language triggers ('create issue', 'discover issues', 'find issues') and command-style triggers ('issue:new', 'issue:discover', 'issue:discover-by-prompt'). Good coverage of terms users would naturally say.

3 / 3

Distinctiveness Conflict Risk

The combination of issue discovery via multi-perspective analysis and issue creation from GitHub/text is a clear niche. The specific command triggers like 'issue:new' and 'issue:discover' make it highly distinct and unlikely to conflict with other skills.

3 / 3

Total

12

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

10

/

11

Passed

Repository
catlog22/Claude-Code-Workflow
Reviewed

Table of Contents

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