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fla-design-coverage

Define supported inputs, numerical budgets, routing, and validation before designing an FLA kernel or numerical change.

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./.agents/skills/fla-design-coverage/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

An impressively lean, well-structured policy skill that assumes reader competence and delegates mechanics to well-signaled sibling skills. Its main weakness is actionability: directives name what to record and test but rarely show how, with no code, commands, or worked examples for any step.

Suggestions

Add one short concrete example per major section, e.g., a filled-in group table (effective arguments, oracle, tolerances, outcome) or a snippet showing an enforced input-norm bound check at the public entry.

Show how a validation checkpoint is executed and what to do on failure — e.g., the shape of the before/after error-distribution comparison and the steps when the gate is red before landing a candidate.

Give a minimal executable pattern for route-parity testing (identical precision settings, restoring globals) so 'Test parity between routes claiming the same domain' becomes copy-paste actionable.

DimensionReasoningScore

Conciseness

The body is dense requirement prose with zero padding: it assumes competence by using terms like "chunk geometry or anchors", "dtype staging", and "context-parallel" without basic explanation, and every sentence states a contract requirement. It clearly matches the 'lean and efficient; every token earns its place' anchor.

5 / 5

Actionability

There is concrete guidance — "Record the merge-base SHA", "capability and availability helpers from `fla.utils`", "Record precision settings such as `TRITON_F32_DEFAULT`" — but much is abstract directive ("Test parity between routes claiming the same domain", "Trace public entries and defaults") with no code, commands, or examples showing how to execute any step. This fits 'some concrete guidance but incomplete; missing key details' better than the 4 anchor, which expects concrete code or commands.

3 / 5

Workflow Clarity

Four sequenced sections (supported domain → numerical safety → routing → evidence) with embedded validation checkpoints ("asserted by a test", "Keep the corrected gate green before the candidate lands", "test its acceptance boundary and the adjacent rejection"). Not a 5 because the ordering between sections is implicit rather than stated and there is no explicit error-recovery loop when a checkpoint fails.

4 / 5

Progressive Disclosure

The skill is under 50 lines with well-organized sections and no bundle files of its own, so the simple-skill exception applies; implementation mechanics are cleanly delegated to one-level-deep, clearly signaled references ("use fla-dispatch-backends for implementation mechanics", fla-correctness-coverage, fla-optimization-loop, CONTRIBUTING.md). This matches 'clear overview with well-signaled one-level-deep references; easy navigation'.

5 / 5

Total

17

/

20

Passed

Description

75%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 solid description that names concrete actions, an explicit trigger situation, and a distinctive niche. It sits a notch below the best examples because the trigger coverage is narrow and it under-represents parts of the skill's scope (evidence, compatibility, baseline performance).

Suggestions

Add one or two more trigger phrases covering the other entry points the body handles, e.g., 'or when changing backend routing, defaults, or tolerances'.

Mention the evidence/baseline aspect (e.g., 'record correctness and performance baselines') so the description reflects the full scope of the skill.

DimensionReasoningScore

Specificity

The description lists four concrete action objects — "Define supported inputs, numerical budgets, routing, and validation" — in a named domain, matching the 'several specific actions; minor gaps' anchor. It is not a 5 because it omits other substantive things the skill covers (e.g., evidence selection, baseline recording, compatibility policy), and not a 3 because it goes well beyond 1-2 actions.

4 / 5

Completeness

It answers both 'what' ("Define supported inputs, numerical budgets, routing, and validation") and 'when' via an explicit trigger equivalent ("before designing an FLA kernel or numerical change"). Not a 5 because the when-clause covers only two trigger situations and could be more specific (e.g., backend routing changes or default changes, which the body itself treats as triggers).

4 / 5

Trigger Term Quality

"FLA kernel", "numerical change", "routing", and "validation" are terms a developer in this domain would naturally say, giving good keyword coverage. Not a 5 because common synonyms and variations (e.g., "precision", "tolerance", "backward", "backend") are missing.

4 / 5

Distinctiveness Conflict Risk

"FLA kernel" and "numerical change" establish a clear niche with minimal generic conflict, but the pre-implementation design scope overlaps with closely related sibling skills (fla-dispatch-backends, fla-correctness-coverage, fla-optimization-loop) referenced in the body — minor overlap risk, matching the 4 anchor rather than the clearly-distinct 5.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 6 suspicious

Warning

Total

15

/

16

Passed

Repository

fla-org/flash-linear-attention

Path

.agents/skills/fla-design-coverage/SKILL.md

Reviewed

Table of Contents

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