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lightrun-live-runtime-debugging

Diagnose live bugs and incidents that require runtime evidence from a running service using Lightrun MCP. Use when static analysis or logs cannot explain the failure mechanism, when a hypothesis must be tested against live values or control flow, or when resuming Lightrun async actions. For latency, timeout, deadline, SLO, or hang diagnosis, use lightrun-slow-execution-diagnosis when available; if unavailable, continue here with best-effort evidence. Do not use for one-off production measurements (use lightrun-ask-prod when available; otherwise report the measurement-scope gap), pull-request review, code changes, setup, or deployment.

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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 instruction-only skill: it is token-lean, sequenced with explicit gates and error-recovery feedback loops, and keeps detailed protocol material in two clearly signaled, conditionally-loaded reference files. Remaining gains are marginal — tightening the overlapping no-hit/retargeting bullets and adding one worked example of hypothesis-to-signal mapping.

DimensionReasoningScore

Conciseness

The body is lean and directive throughout — terse imperative bullets with no explanation of concepts Claude already knows — e.g., 'Place each probe on an executable location tied to a hypothesis discriminator'. It falls short of anchor 5 due to minor redundancy: the timeout/no-hit handling rules in 'Action Error Mitigation' restate source-retargeting guidance across several overlapping bullets, and the cleanup disposition appears twice ('Include each owned action's cancelled, retained, or terminal disposition in the handoff' and 'Append cleanup disposition only when owned actions exist').

4 / 5

Actionability

For an instruction-only skill the guidance is mostly concrete and executable: a quantified async activation gate ('after two consecutive no-hit/timeouts from correctly targeted synchronous captures'), exact blocker/retry reporting fields, a troubleshooting URL, and four fully-specified outcome branches with required fields. It is not anchor 5 because key operational specifics are necessarily deferred to dynamic MCP schemas and reference files, and some directives remain abstract ('Rank the smallest plausible hypothesis set and the signal that would strengthen or weaken each hypothesis') without a worked example.

4 / 5

Workflow Clarity

The 'Quick Use Guide' gives a clearly numbered seven-step sequence with explicit validation gates (preflight gate, async activation gate, cleanup gate), and 'Action Error Mitigation' provides genuine feedback loops for error recovery — verify timeout settings, widen the collection window, retarget source/location/signal/hypothesis before any repeat reproduction, and re-check source targeting after no-hit outcomes. This matches the anchor 5 pattern of explicit validation steps plus fix-and-retry loops, and the safety rule 'Never cancel any other action' guards the one risky operation class.

5 / 5

Progressive Disclosure

SKILL.md acts as a clear overview with two well-signaled, one-level-deep references loaded exactly at point of need: 'read [MCP tool discovery](references/mcp-tool-discovery.md) and complete its source-discovery preflight' before first capture, and 'read [Async runtime actions](references/async-actions.md) before creating, polling, retrieving, or cancelling actions'. Both referenced files exist in the bundle, content is appropriately split (shared discovery rules and async protocol details out of the main file), and navigation is easy — matching anchor 5.

5 / 5

Total

18

/

20

Passed

Description

87%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 description: it clearly states what the skill does and when to use it, routes overlapping use cases to sibling skills with fallback handling, and declares explicit exclusions. The capability list is slightly abstract relative to the strongest examples, keeping specificity and trigger-term coverage at 4 rather than 5.

DimensionReasoningScore

Specificity

The description lists several concrete capabilities — 'Diagnose live bugs and incidents that require runtime evidence from a running service using Lightrun MCP', testing 'a hypothesis... against live values or control flow', and 'resuming Lightrun async actions'. It stops short of anchor 5 because the actions stay at the diagnosis-workflow level rather than enumerating comprehensive concrete operations (e.g., capturing snapshots, logging arguments, measuring timings).

4 / 5

Completeness

It explicitly answers what ('Diagnose live bugs and incidents that require runtime evidence from a running service using Lightrun MCP') and when ('Use when static analysis or logs cannot explain the failure mechanism, when a hypothesis must be tested against live values or control flow, or when resuming Lightrun async actions'), with concrete trigger phrases and an explicit negative boundary ('Do not use for one-off production measurements... pull-request review, code changes, setup, or deployment'). This matches anchor 5; anchor 4 would require the 'when' to be less explicit than it is.

5 / 5

Trigger Term Quality

Good natural-keyword coverage: 'live bugs', 'incidents', 'static analysis or logs cannot explain the failure mechanism', 'latency, timeout, deadline, SLO, or hang', plus sibling-skill routing terms. A few natural phrasings users might say are absent (e.g., 'production debugging', 'snapshot', 'can't reproduce'), so it fits anchor 4 rather than the comprehensive synonym coverage of anchor 5.

4 / 5

Distinctiveness Conflict Risk

Clear niche (live runtime debugging via Lightrun MCP) with explicit routing to sibling skills ('use lightrun-slow-execution-diagnosis when available', 'use lightrun-ask-prod when available') including fallback behavior, plus explicit exclusions. Minimal conflict risk, matching anchor 5.

5 / 5

Total

18

/

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-live-runtime-debugging/SKILL.md

Reviewed

Table of Contents

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