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metric-diagnostics

Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy.

61

Quality

72%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./packages/opencode/src/skill/builtin/.bundle/data-analytics/workflows/metric-diagnostics/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

66%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.

The skill presents a well-sequenced diagnostic workflow with strong validation checkpoints and explicit handoff rules to related skills. It is weaker on token efficiency (repeated handoffs and overlapping source-discovery guidance) and actionability (abstract direction where a worked example or decomposition template would make the guidance executable).

Suggestions

State each $skill handoff once (at the step where it matters) and drop the "Related Skills" preamble to remove triplicated guidance and reduce token cost.

Add one compact worked example of a driver decomposition (e.g., a movement split into contribution shares with a reconciled residual) to make step 5's abstract sizing direction concrete and executable.

Move the explanation-mode catalog in step 4 and the source-access guardrail prose into a one-level-deep reference file so SKILL.md stays a lean overview.

DimensionReasoningScore

Conciseness

The body is mostly efficient but carries repetition: the $gather-business-context handoff is stated three times ("Related Skills", step 1, step 4), and source-discovery guidance ("starting points, not stopping points") appears in both the configuration and step 2 sections, so it could be tightened without loss.

3 / 5

Actionability

Some concrete guidance exists ("grain, aggregation logic, filters, joins, exclusions, freshness, lineage"; the four explanation modes), but much of the direction is abstract ("size each major driver with the strongest readily available evidence") with no worked example or query/decomposition template, so it reads as incomplete rather than fully executable guidance.

3 / 5

Workflow Clarity

The six-step workflow is clearly sequenced with explicit validation gates ("Before explaining the movement, confirm...", "Do not search for causes until the size, timing, and scope of the pattern are verified") and a pre-handoff completeness checklist, matching the top anchor for sequence plus checkpoints.

5 / 5

Progressive Disclosure

No bundle files exist and the body is well-sectioned with clear headers, so navigation is good; however, at ~130 lines monolithic, content such as the explanation-mode catalog and the source-access guardrail could live in one-level-deep reference files, which is a minor organization gap against the top anchor.

4 / 5

Total

15

/

20

Passed

Description

78%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.

The description is concise, in third person, and cleanly separates what the skill does from when to use it, with natural trigger terms. Its main gap is specificity of capabilities — the single 'diagnose' verb undersells the multi-step diagnostic workflow the skill actually performs.

DimensionReasoningScore

Specificity

"Diagnose why a metric changed or differs from expectation" names the domain and the core action, but does not enumerate multiple concrete operations (e.g., reproduce, quantify, validate drivers), matching the '1-2 concrete actions' anchor rather than the 'several specific actions' anchor above.

3 / 5

Completeness

It explicitly answers both "what" ("Diagnose why a metric changed or differs from expectation") and "when" ("Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy") with concrete trigger phrases, mirroring the top anchor's example pattern.

5 / 5

Trigger Term Quality

"metric movement, anomaly, gap, or discrepancy" provides good natural trigger coverage users would plausibly say, though common synonyms like "KPI", "spike", or "drop/increase" are missing, keeping it below the comprehensive anchor.

4 / 5

Distinctiveness Conflict Risk

Metric-change diagnosis is a fairly distinct niche with specific triggers ("movement, anomaly, gap, discrepancy"), but it retains minor overlap risk with general data-analysis or data-quality skills, so it does not fully reach the clear-niche anchor.

4 / 5

Total

16

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
XiaomiMiMo/MiMo-Code
Reviewed

Table of Contents

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