code-runtime-diagnose

code-runtime-diagnose is a skill for Claude Code, Codex from anpy-j/graylog-mcp. It costs 82 tokens per session (719 once invoked), scanned A, original, MIT.

Instructions for diagnosing runtime bugs by connecting application source code with Graylog log events. They describe how to trace code paths, find useful log text and identifiers, and compare the code with observed runtime evidence.

In plain words
What is it for?
Investigating missing results, failed callbacks, stuck asynchronous jobs, inconsistent data, and other issues by following logs across code paths and related identifiers.
Why use it?
They help distinguish what the code suggests from what actually happened in production or another running environment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Investigating missing results, failed callbacks, stuck asynchronous jobs, inconsistent data, and other issues by following logs across code paths and related identifiers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anpy-j/graylog-mcp/code-runtime-diagnose
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add anpy-j/graylog-mcp --skill code-runtime-diagnose
Clone the repo
git clone --depth 1 https://github.com/anpy-j/graylog-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for code-runtime-diagnose

README.md
[![agentmods](https://agentmods.dev/badge/skills/anpy-j/graylog-mcp/code-runtime-diagnose/github.svg)](https://agentmods.dev/skills/anpy-j/graylog-mcp/code-runtime-diagnose)
Your own site
<a href="https://agentmods.dev/skills/anpy-j/graylog-mcp/code-runtime-diagnose"><img src="https://agentmods.dev/badge/skills/anpy-j/graylog-mcp/code-runtime-diagnose/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for code-runtime-diagnose

Your own site · 80×15
<a href="https://agentmods.dev/skills/anpy-j/graylog-mcp/code-runtime-diagnose"><img src="https://agentmods.dev/badge/skills/anpy-j/graylog-mcp/code-runtime-diagnose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 719 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00082 $0.00719
Opus 5.5 $0.00033 $0.00288
Sonnet 5.5 $0.00016 $0.00144
Haiku 4.5 $0.00008 $0.00072

Measured 1mo ago against content hash b44a85d9bc23, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-runtime-diagnose scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/code-runtime-diagnose/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code runtime diagnosis

Connect static code paths to runtime evidence through the Graylog Agent Toolkit MCP. Keep code inference separate from observed log facts.

Workflow

  1. Confirm the environment, symptom time, timezone, business identifier, and requested scope. Begin read-only unless the user also requests a fix.
  2. Locate the entrypoint and follow the relevant branches, async submissions, callbacks, consumers, and persistence boundaries.
  3. Extract stable literal fragments from relevant log statements. Prefer text such as 收到回调, callback handle success, or a structured stage= value over class names or variable-only text.
  4. Collect known identifiers such as studentExamId, studentId, taskId, requestNo, traceId, requestId, itemKey, ossKey, and bizType.
  5. If a matching business profile exists, read it with graylog_get_profile. Profiles add vocabulary, entrypoints, stages, and correlation keys; they do not replace code inspection.
  6. Call graylog_diagnose_code_logs with the literals, identifiers, profile, and the narrowest useful time range. If exact absolute times are unavailable, use a short relative range and state it.
  7. Follow identifiers discovered by the first result across async boundaries. Use graylog_search_messages only for a targeted raw Lucene query that the correlation tool cannot express.
  8. Map important events back to source files and branch conditions. Identify the first missing, failed, skipped, or contradictory stage.
  9. Report the timeline and the smallest next verification step. Do not edit code, rerun a job, or change data unless the user authorized it.

Query rules

  • Use UTC RFC3339 timestamps for MCP absolute ranges; translate user-local time explicitly.
  • Search stable literals and exact identifiers together when that narrows results without hiding alternate branches.
  • Start with at most a few strong terms. Expand through returned correlation values instead of using a broad wildcard query.
  • Treat no results as an observation, not proof that code did not execute. Check environment, time range, timezone, stream, ingestion, and literal accuracy.
  • Never place Graylog credentials, session IDs, cookies, authorization headers, or signed URL secrets in prompts or reports.

Read the full file on GitHub · 62 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 62 lines · 82 tokens per session scan A b44a85d9bc23

Subscribe to this mod's changes

code-runtime-diagnose is a skill published in the GitHub repository anpy-j/graylog-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 82 tokens to every session and 719 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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