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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 latency, timeout, deadline, SLO, or hang diagnosis to lightrun-slow-execution-diagnosis when available; route other diagnosis, or fallback when that skill is unavailable, to lightrun-live-runtime-debugging when available. If neither diagnosis skill is available, report the scope gap.

Quality

94%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

85%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 well-engineered procedural skill: the six-step flow has explicit validation gates, retry conditions, and error-recovery feedback loops, and the schema-driven example honestly handles the dynamic MCP tool-discovery reality. Structure and reference usage are exemplary; the only slack is minor wordiness in a few conditional rules and the telemetry preamble.

Suggestions

Tighten the wordiest conditional rules (e.g., the default-duration rule and the owned-action rule in step 5) into shorter imperative clauses or a small table like the capability-selection one.

Fold the telemetry section into a two-line note at the top or bottom so the body opens directly with the task workflow.

DimensionReasoningScore

Conciseness

The body is dense and directive with no concept explanations Claude already knows (no 'what is production' padding), and steps like 'Locate the relevant code' carry only decision-relevant bullets. A few conditional sentences are wordy ('Use the default duration only when it covers expected signal latency and fits task or session bounds; otherwise use an explicit bounded window and state why'; 'Treat only actions created or explicitly inherited for this request as owned') and the telemetry preamble adds non-task tokens, keeping it just below the every-token-earns-its-place anchor.

4 / 5

Actionability

Concrete guidance throughout: a capability-selection table ('What is the current value of X? → Snapshot/expression capture'), source-selection rules, an error-handling table, and a fully worked example (question → selection → call → validation → representative result → answer). The illustrative call 'measure_duration({...})' is not literally executable, but the disclaimer is explicit and justified by the skill's schema-driven discovery model ('Take real tool names and parameters from the exposed MCP schema'), so guidance is actionable with only the runtime-dependent invocation as an inherent gap.

4 / 5

Workflow Clarity

A clear six-step sequence with explicit validation gates and feedback loops: 'If no executable location can be identified, do not capture; return the blocker, required remediation, and retry condition', source preflight pass/fail criteria, schema-status branching ('new results → retrieve them; non-terminal without new results → wait within the bounded window... terminal → report the blocker or empty result'), and 'After repeated no-data or low-information results, revalidate or change the source, code location, signal, or window'. An error-handling table adds recovery actions. This matches the anchor for explicit validation steps with error-recovery feedback loops; it is not the level-4 anchor because checkpoints are explicit rather than mostly present.

5 / 5

Progressive Disclosure

The single bundle reference (references/mcp-tool-discovery.md) exists, is well-structured (64 lines with matching headings), is referenced twice with clear signals including a working anchor link ('Source discovery (preflight)'), and is exactly one level deep. The core workflow and worked example are appropriately inline, and discovery/preflight detail is correctly offloaded — matching the clear-overview, well-signaled one-level-deep-references anchor.

5 / 5

Total

18

/

20

Passed

Description

100%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.

An exemplary description: explicit what and when with natural trigger-phrase examples, negative scope boundaries, and explicit routing to sibling diagnosis skills with fallback handling. Third-person, concrete, and no over-claims.

DimensionReasoningScore

Specificity

It lists multiple concrete measurement actions — 'current variable values, execution durations, hit counts, and value distributions' — via the concrete mechanism 'instrumenting running services with Lightrun MCP tools', in third-person voice. Coverage matches the capability set in the body comprehensively, fitting the multiple-specific-concrete-actions anchor rather than the minor-gaps anchor below it.

5 / 5

Completeness

It explicitly answers both: what ('Answer questions about live production system behavior — current variable values, execution durations, hit counts, and value distributions — by instrumenting running services') and when ('Use when the question requires live runtime data rather than static code analysis' plus concrete trigger examples), and adds when-not-to-use guidance. This is the clear both-what-and-when-with-concrete-trigger-phrases anchor.

5 / 5

Trigger Term Quality

It includes natural user phrasings users would actually say — '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?' — plus synonyms ('live production', 'live runtime data', 'in production'). This matches the comprehensive-natural-terms anchor; it does not fall to 4 since synonym and phrase coverage is broad, not just good.

5 / 5

Distinctiveness Conflict Risk

It carves a clear niche (live runtime measurement vs static code analysis), explicitly excludes overlapping cases ('Do not use for incident diagnosis, pull-request review, code changes, setup, or deployment'), and routes diagnosis questions to named sibling skills with fallback logic. Minimal conflict risk — matching the clear-niche-with-distinct-triggers anchor.

5 / 5

Total

20

/

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

lightrun-platform/lightrun-ai

Path

skills/lightrun-ask-prod/SKILL.md

Reviewed

Table of Contents

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