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datadog

Use when the user says "check Datadog", "查 Datadog", "查日志", "check logs", "crash logs", "查 crash", "gateway crash", "查告警", "check alerts", "check metrics", or needs to investigate production issues via Datadog Logs API.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

High

Do not use without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

An exemplary operational skill body: executable copy-paste queries, lean reference tables, and a sequenced investigation playbook with conditional correlation logic. It assumes Claude's competence throughout and avoids concept-explanation padding.

DimensionReasoningScore

Conciseness

The body is lean and operationally dense — no preamble explaining what Datadog or curl is — and every section (queries, parsing, reference tables, playbook, rules) earns its place; the repeated header blocks are unavoidable for standalone copy-paste curl examples.

3 / 3

Actionability

It provides fully executable curl commands against the real v2 logs/events/search endpoint with concrete JSON payloads, plus an inline python3 parser, all copy-paste ready with real service names and tag filters.

3 / 3

Workflow Clarity

The Investigation Playbook gives a clear 5-step sequence with conditional correlation logic (correlate crashes with image_tag deploys; if invalid_auth, look for slack_token_health_check_invalidated); being read-only, no destructive/batch validation cap applies.

3 / 3

Progressive Disclosure

The single SKILL.md is well-organized into clearly headed, navigable sections (Authentication, API Base, Common Queries, Parsing, References, Playbook, Rules) with no nested or deep references and no bundle files requiring navigation.

3 / 3

Total

12

/

12

Passed

Description

90%

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, trigger-rich description that answers both what and when with an explicit Use-when clause and bilingual natural-language triggers. The only weakness is that capability specificity rests on a single umbrella action (investigate production issues) rather than an enumerated set of distinct actions.

Suggestions

Add one explicit enumeration of concrete capabilities after the triggers, e.g. "Queries crash events, stderr output, startup/recovery events, and Slack token health via the Datadog Logs API" to lift specificity from one umbrella action to multiple named actions.

DimensionReasoningScore

Specificity

The description names the domain ("investigate production issues via Datadog Logs API") but frames the rest as user utterances rather than distinct capabilities, so it lists one concrete action with many triggers rather than a comprehensive action set.

2 / 3

Completeness

It states what the skill does ("investigate production issues via Datadog Logs API") and pairs it with an explicit "Use when the user says..." trigger clause, answering both what and when.

3 / 3

Trigger Term Quality

It packs in natural phrases a user would actually say — "check Datadog", "check logs", "crash logs", "gateway crash", "check alerts", "check metrics" — with bilingual variants ("查日志", "查告警", "查 crash"), giving strong coverage.

3 / 3

Distinctiveness Conflict Risk

The Datadog Logs API / Nexu production-investigation niche with highly specific triggers (e.g. "gateway crash", "查告警") is clearly distinguishable and unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

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
nexu-io/nexu
Reviewed

Table of Contents

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