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testland/flake-dashboard-author

Builds a persistent flakiness infrastructure dashboard from JUnit XML or JSON CI run history: defines the flake-rate metric (failures per test over a configurable window), authors the data model, generates a Grafana time-series panel JSON or configures a Datadog CI Visibility view, derives the quarantine-candidate query, and wires trend alerts. Also generates the periodic (weekly / monthly) test-suite trend report - total runs, suite duration, flakiness rate, top failing tests, time-to-green per PR, week-over-week deltas - as a markdown summary for a team Slack channel or wiki page. Use when a team needs a long-lived observability surface for test reliability, or a scheduled comparable health report on top of it.

65

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Overview
Quality
Evals
Security
Files

Quality

Content

71%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.

A thorough, largely actionable skill body with concrete code and a clear step sequence, weakened by references to bundle files that are not shipped and a monolithic structure that could be split. Conciseness is good with minor trimmable prose.

Suggestions

Add the referenced bundle files (scripts/parse_junit.py, scripts/ingest_playwright_json.js, scripts/quarantine_candidates.sql, dashboards/flakiness-overview.json) or remove the invocations so the worked example is fully executable.

Move the full Grafana panel JSON and quarantine SQL into separate reference files linked from SKILL.md to improve progressive disclosure and reduce inline bulk.

Trim the terminology note and 'Cadence and caveats' prose to the strictly necessary detail to tighten conciseness.

DimensionReasoningScore

Conciseness

The body is dense with concrete SQL, JSON, and bash, with most tokens earning their place, but the terminology note, 'Cadence and caveats' prose, and the full inline markdown report template include minor over-explanation that could be trimmed.

4 / 5

Actionability

It provides copy-paste-ready SQL schema, Grafana panel JSON, Datadog queries, and a worked bash example, but several invoked scripts (scripts/parse_junit.py, scripts/ingest_playwright_json.js, scripts/quarantine_candidates.sql, dashboards/flakiness-overview.json) are not provided in the bundle, leaving minor executability gaps.

4 / 5

Workflow Clarity

A clear six-step sequence (Step 1-6) plus a worked bootstrap example and step-by-step alert setup gives a strong ordering, but there are no explicit validate-then-fix feedback loops, leaving minor checkpoint gaps.

4 / 5

Progressive Disclosure

The file is well-sectioned internally but is a single monolithic document with content (full Grafana JSON, SQL queries, report template) that could live in separate reference files, and it references bundle scripts/dashboards that do not exist in references/, scripts/, or assets/, so references are present but not backed by real files.

3 / 5

Total

15

/

20

Passed

Description

88%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 strong, third-person description that comprehensively lists concrete capabilities and pairs them with an explicit 'Use when...' trigger clause. Keyword coverage is good but could add synonyms and file extensions to reach the top anchor.

DimensionReasoningScore

Specificity

The description enumerates many concrete actions in third person ('Builds...', 'defines the flake-rate metric', 'authors the data model', 'generates a Grafana time-series panel JSON', 'derives the quarantine-candidate query', 'wires trend alerts'), giving comprehensive coverage of what the skill does.

5 / 5

Completeness

It explicitly answers both 'what' (the detailed action list) and 'when' ('Use when a team needs a long-lived observability surface for test reliability, or a scheduled comparable health report on top of it.') with concrete trigger phrases.

5 / 5

Trigger Term Quality

It includes natural terms users would say ('flakiness', 'dashboard', 'grafana', 'datadog', 'junit', 'test reliability', 'CI run history') plus metadata keywords, but omits some common synonyms ('flaky tests') and explicit file extensions (.xml, .json), leaving a few natural terms missing.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (persistent flakiness infrastructure dashboard with Grafana/Datadog/JUnit triggers) with mostly distinct triggers, though the 'scheduled comparable health report' clause could overlap with a sibling report skill, leaving minor overlap risk.

4 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

referenced_paths_exist

Referenced path issues: 3 missing

Warning

Total

14

/

16

Passed

Reviewed

Table of Contents

DiscoveryImplementationValidation