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team-perf-opt

Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt".

50

Quality

55%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./.codex/skills/team-perf-opt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

This is a well-structured orchestration skill that provides highly actionable, concrete guidance for coordinating a multi-agent performance optimization pipeline. The delegation lock, spawn templates, error handling table, and agent coordination semantics are all specific and executable. Minor verbosity in a few sections (model selection rationale, some redundancy between architecture diagram and pipeline descriptions) prevents a perfect conciseness score, but overall token efficiency is reasonable given the complexity of the orchestration being described.

DimensionReasoningScore

Conciseness

The skill is fairly dense and information-rich, but includes some sections that could be tightened—e.g., the Model Selection Guide rationale column restates obvious points, and the architecture ASCII diagram is somewhat redundant with the pipeline descriptions below it. However, most content is non-trivial orchestration logic that Claude wouldn't inherently know.

2 / 3

Actionability

Provides concrete spawn_agent templates with exact parameter names, specific tool call verdicts in the delegation lock table, explicit timeout values (1800000ms), named agent targeting examples, and copy-paste-ready completion action code. The guidance is highly specific and executable.

3 / 3

Workflow Clarity

The pipeline modes (single, fan-out, independent) are clearly sequenced with explicit phase ordering. Validation checkpoints are present: agent health checks via list_agents, benchmark regression detection triggering FIX tasks, review-fix cycle limits with user escalation, and timeout handling with STATUS_CHECK → FINALIZE → close_agent progression.

3 / 3

Progressive Disclosure

The SKILL.md serves as a clear router/overview with well-signaled one-level-deep references to role files (roles/coordinator/role.md, etc.) and spec files (specs/pipelines.md, specs/team-config.json). The role registry table provides a clean navigation index. Content is appropriately split between the overview and referenced role/spec files.

3 / 3

Total

11

/

12

Passed

Description

25%

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 description reads more like an internal architecture summary than a user-facing skill description. It focuses on implementation details (coordinator, workers, fan-out modes) rather than concrete user-facing capabilities, and relies on an artificial trigger command rather than natural language keywords. The domain of 'performance optimization' is too broad without specifying what kind of performance optimization is being done.

Suggestions

Replace the artificial trigger 'team perf-opt' with natural language triggers users would actually say, e.g., 'Use when the user asks to optimize performance, speed up code, reduce latency, or profile bottlenecks'.

Specify concrete actions the skill performs, e.g., 'Profiles code execution, identifies bottlenecks, parallelizes workloads, and recommends caching strategies' instead of describing internal architecture.

Narrow the domain scope to clarify what type of performance optimization this covers (e.g., backend API, frontend rendering, database queries) to reduce conflict risk with other potential optimization skills.

DimensionReasoningScore

Specificity

The description uses vague language like 'performance optimization' and 'orchestrates pipeline' without specifying concrete actions. It describes architecture (coordinator, workers, fan-out modes) rather than what the skill actually does for the user.

1 / 3

Completeness

It partially addresses 'what' (performance optimization with parallel modes) and includes a trigger clause ('Triggers on "team perf-opt"'), but the trigger is an artificial command rather than a natural usage scenario. The 'when' is technically present but not meaningful for real skill selection.

2 / 3

Trigger Term Quality

The trigger term 'team perf-opt' is artificial jargon that no user would naturally say. Terms like 'coordinator', 'fan-out', and 'pipeline' are internal implementation details, not natural user language. A user seeking performance optimization would say things like 'speed up', 'optimize performance', 'slow code', etc.

1 / 3

Distinctiveness Conflict Risk

'Performance optimization' is broad and could overlap with many skills (database optimization, frontend performance, build optimization, etc.). The artificial trigger 'team perf-opt' provides some distinctiveness but only because it's a custom command, not because the domain is well-scoped.

2 / 3

Total

6

/

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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