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lightrun-ask-prod

Answer questions about live production system behavior — current variable values, execution durations, hit counts, and value distributions — by instrumenting running services with Lightrun MCP tools. Use when the question requires live runtime data rather than static code analysis (e.g. "show recent requests to this endpoint", "show the runtime distribution for this operation", "what values appear for this expression in production?", "which branch runs for customer X?"). Do not use for incident diagnosis, pull-request review, code changes, setup, or deployment. Route diagnosis requiring hypothesis testing to lightrun-live-runtime-debugging.

86

1.92x
Quality

100%

Does it follow best practices?

Impact

77%

1.92x

Average score across 1 eval scenario

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

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

The content is concise, actionable, and well-structured with a clear sequenced workflow, explicit validation gates, and a single well-signaled reference. It adds only what Claude would not already know and organizes it for easy navigation.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — it never explains basic concepts, uses compact tables and a tight schema-driven example, and every section earns its place; only minor boilerplate phrases recur.

3 / 3

Actionability

Provides a concrete question→capability mapping table, specific code-location heuristics, selection logic, and a parameterized illustrative call with a representative result — actionable guidance rather than abstract direction.

3 / 3

Workflow Clarity

A clearly sequenced six-step flow with explicit validation checkpoints ("If no executable location can be identified, do not capture; return the blocker...") and an error-handling table with feedback loops for stale/duplicate actions.

3 / 3

Progressive Disclosure

SKILL.md is an overview that signals a single one-level-deep reference (references/mcp-tool-discovery.md, a real file, linked with a section anchor), keeping shared discovery rules out of the main body.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%Scale 1-3

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 specific, trigger-rich, and complete, answering both what the skill does and when to use it while carving out a distinct niche with explicit exclusions and routing. It avoids verbosity and over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — "current variable values, execution durations, hit counts, and value distributions" and "instrumenting running services" — matching the anchor for several specific concrete actions.

3 / 3

Completeness

Explicitly states both what it does ("Answer questions about live production system behavior... by instrumenting running services") and when to use it ("Use when the question requires live runtime data rather than static code analysis"), with explicit anti-triggers.

3 / 3

Trigger Term Quality

Embeds natural user phrasings such as "show recent requests to this endpoint", "what values appear for this expression in production?", and "which branch runs for customer X?" — the kind of phrases a user would actually say.

3 / 3

Distinctiveness Conflict Risk

Clear niche (live runtime data), explicit exclusions ("Do not use for incident diagnosis, pull-request review, code changes, setup, or deployment"), and routing to a sibling skill make conflict unlikely.

3 / 3

Total

12

/

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
lightrun-platform/lightrun-ai
Reviewed

Table of Contents

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