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otel-queries

Guidance for querying and interpreting Copilot and agentic workflow OpenTelemetry token and execution metrics.

58

Quality

66%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./.github/skills/otel-queries/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.

The body is exceptionally concise and well-structured for a simple instruction-only skill, with no unnecessary explanation or external references. Its main weakness is actionability: the guidance tells Claude what to summarize but not how to execute the queries or aggregations.

Suggestions

Add a concrete example for inspecting the JSONL export, such as a jq snippet or a small Python snippet that sums token counts by model and agent step.

Document the key field names present in the COPILOT_OTEL_FILE_EXPORTER_PATH records so aggregation targets are unambiguous.

Optionally include a one-line expected-output example so Claude knows what a 'summarized' result should look like.

DimensionReasoningScore

Conciseness

The body is a lean ~10 lines with no concept over-explanation, assuming Claude already knows OTEL/JSONL, so every token earns its place per the 'lean and efficient' anchor.

5 / 5

Actionability

Bullets like 'Summarize token counts by model, agent step, and request type' give concrete direction on what to summarize, but provide no executable query examples, field names, or jq/aggregation snippets, leaving key execution details missing.

3 / 5

Workflow Clarity

As a simple read-only single-purpose skill the action is unambiguous and well-organized, but the bullets read as guiding principles rather than a crisp sequenced workflow, landing just below the simple-skill 5 anchor.

4 / 5

Progressive Disclosure

The skill is under 50 lines with no bundle files and no need for external references, and its intro plus 'Guidance' section are well-organized, satisfying the simple-skill exception for progressive disclosure.

5 / 5

Total

17

/

20

Passed

Description

53%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 clear and reasonably specific about its OTEL telemetry niche but lacks an explicit 'Use when...' trigger clause, which caps completeness and keeps trigger-term coverage from scoring higher. It is distinct from most other skills but would benefit from natural-language trigger phrases and synonyms.

Suggestions

Add an explicit 'Use when...' clause listing concrete triggers (e.g., 'Use when investigating Copilot or agentic workflow token usage, model usage, execution timing, or exported JSONL telemetry files').

Include natural synonyms and file extensions users actually say, such as 'OTel', 'token usage', and '.jsonl exports'.

Spell out one or two more concrete actions (e.g., 'summarize token counts by model and agent step') to lift specificity toward comprehensive coverage.

DimensionReasoningScore

Specificity

Quotes 'querying and interpreting ... OpenTelemetry token and execution metrics' name the domain plus two concrete actions but stop short of comprehensive coverage, matching the anchor for naming a domain with 1-2 concrete actions.

3 / 5

Completeness

The description gives a clear 'what' (querying and interpreting OTEL metrics) but includes no 'Use when...' trigger clause, so per the rubric cap completeness stays at 3.

3 / 5

Trigger Term Quality

Terms like 'Copilot', 'agentic workflow', 'OpenTelemetry', 'token', and 'execution metrics' are relevant but lean technical, missing common variations such as 'OTel', 'token usage', or 'JSONL export files'.

3 / 5

Distinctiveness Conflict Risk

The Copilot/agentic-workflow OpenTelemetry niche is mostly distinct with only minor overlap risk against a generic telemetry-analysis skill, fitting the 'mostly distinct' anchor rather than the fully niche-bound 5.

4 / 5

Total

13

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
dotnet/maui
Reviewed

Table of Contents

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