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csv-wave-pipeline

Requirement planning to wave-based CSV execution pipeline. Decomposes requirement into dependency-sorted CSV tasks, computes execution waves, runs wave-by-wave via spawn_agents_on_csv with cross-wave context propagation.

50

Quality

41%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.codex/skills/csv-wave-pipeline/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Discovery

27%

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 technically detailed about its internal mechanism but fails as a skill selector because it uses implementation jargon rather than user-facing language, lacks any explicit 'Use when...' trigger guidance, and would be nearly impossible for Claude to match against natural user requests. It reads more like an internal architecture note than a skill description.

Suggestions

Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user wants to break down a complex requirement into parallel tasks, plan multi-step execution, or orchestrate dependent subtasks.'

Replace implementation jargon like 'spawn_agents_on_csv' and 'cross-wave context propagation' with user-facing language such as 'parallel task execution', 'dependency management', and 'multi-step task orchestration'.

Clarify the domain and scope more concretely—what kind of requirements? Software features, project plans, data processing pipelines? This would reduce conflict risk with other planning-related skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: decomposes requirements into dependency-sorted CSV tasks, computes execution waves, runs wave-by-wave via spawn_agents_on_csv, and propagates cross-wave context.

3 / 3

Completeness

Describes what it does (decomposes requirements, computes waves, runs tasks) but completely lacks any 'Use when...' clause or explicit trigger guidance, which per the rubric caps completeness at 2, and the 'what' is also described in implementation-centric rather than user-facing terms, pushing it to 1.

1 / 3

Trigger Term Quality

Uses highly technical jargon like 'wave-based CSV execution pipeline', 'spawn_agents_on_csv', 'cross-wave context propagation' that users would never naturally say. Missing natural trigger terms a user might use like 'plan tasks', 'break down requirements', or 'parallel execution'.

1 / 3

Distinctiveness Conflict Risk

The mention of 'spawn_agents_on_csv' and 'wave-based' execution is fairly niche, but 'requirement planning' is broad enough to overlap with general planning or task decomposition skills. The technical specificity helps somewhat but the vague 'requirement planning' prefix introduces conflict risk.

2 / 3

Total

7

/

12

Passed

Implementation

55%

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

This skill is highly actionable with excellent workflow clarity — every phase has concrete code, clear sequencing, validation checkpoints, and error recovery. However, it is severely over-long for a SKILL.md, cramming ~600+ lines of implementation detail (CSV parsers, topological sort, full instruction templates, handoff intake) into a single file with no progressive disclosure. The content would be far more effective as a concise overview with supporting reference files.

Suggestions

Extract CSV utility functions (parseCsv, parseCsvLine, csvEscape, updateMasterCsvRow) into a separate UTILS.md or reference file, and link to it from the main skill.

Move the detailed instruction template builder and its discovery type documentation into a separate AGENT_INSTRUCTIONS.md file.

Move the handoff intake section and detailed CSV schema documentation into separate reference files (HANDOFF.md, SCHEMA.md), keeping only a brief summary and link in the main skill.

Trim explanatory comments in code blocks — Claude can infer algorithm intent from well-named variables and the surrounding context without inline narration like '// Algorithm: 1. Build in-degree map...'.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~600+ lines. It includes full CSV parsing utility functions, complete instruction template strings, extensive code for every phase, and detailed CSV schema examples that could be in separate reference files. Much of this (CSV parsing, topological sort algorithms, session management boilerplate) is implementation detail Claude could derive from a concise specification.

1 / 3

Actionability

The skill provides fully executable JavaScript code for every phase: session initialization, wave computation (complete Kahn's algorithm), CSV generation, wave execution with spawn_agents_on_csv calls, result merging, and report generation. The instruction template, output schema, and CSV schemas are all concrete and copy-paste ready.

3 / 3

Workflow Clarity

The three-phase workflow is clearly sequenced with explicit validation checkpoints: user validation after Phase 1, dependency checking before each wave, result merging after each wave, and retry logic for failed tasks. Error handling table covers all failure modes with resolutions. The skip-on-failure pattern and wave ordering rules are explicit.

3 / 3

Progressive Disclosure

Everything is in a single monolithic file with no bundle files or external references. The CSV utility functions, instruction template, handoff intake logic, and detailed CSV schema documentation could all be split into separate reference files. The content is a wall of code and tables that would benefit greatly from progressive disclosure.

1 / 3

Total

8

/

12

Passed

Validation

72%

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

Validation8 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (961 lines); consider splitting into references/ and linking

Warning

allowed_tools_field

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

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

8

/

11

Passed

Repository
catlog22/Claude-Code-Workflow
Reviewed

Table of Contents

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