pipeline-doctor

pipeline-doctor is a skill for Claude Code, Codex from genudo-ai/genudo_mcp. It costs 80 tokens per session (358 once invoked), scanned A, original, MIT.

A troubleshooting workflow for Genudo agents, which are conversational agents configured with stages, instructions, and actions.

In plain words
What is it for?
Analyzing conversations, diagnosing behavior, proposing a minimal fix, and verifying its expected effect. Changes are not pushed without confirmation.
Why use it?
It helps find why an agent gave the wrong response or triggered an action at the wrong time, then identifies the responsible configuration.

Skill for Claude CodeCodex

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

Good fit Analyzing conversations, diagnosing behavior, proposing a minimal fix, and verifying its expected effect. Changes are not pushed without confirmation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/genudo-ai/genudo_mcp/pipeline-doctor
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 genudo-ai/genudo_mcp --skill pipeline-doctor
Clone the repo
git clone --depth 1 https://github.com/genudo-ai/genudo_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 pipeline-doctor

README.md
[![agentmods](https://agentmods.dev/badge/skills/genudo-ai/genudo_mcp/pipeline-doctor/github.svg)](https://agentmods.dev/skills/genudo-ai/genudo_mcp/pipeline-doctor)
Your own site
<a href="https://agentmods.dev/skills/genudo-ai/genudo_mcp/pipeline-doctor"><img src="https://agentmods.dev/badge/skills/genudo-ai/genudo_mcp/pipeline-doctor/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 pipeline-doctor

Your own site · 80×15
<a href="https://agentmods.dev/skills/genudo-ai/genudo_mcp/pipeline-doctor"><img src="https://agentmods.dev/badge/skills/genudo-ai/genudo_mcp/pipeline-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 358 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 $0.00080 $0.00358
Opus 5 $0.00040 $0.00179
Sonnet 5 $0.00016 $0.00072
Haiku 4.5 $0.00008 $0.00036

Measured 12d ago against content hash 9f6d2fd5eeee, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

pipeline-doctor 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 12d 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.

chatgpt/genudo-chatgpt-plugin/skills/pipeline-doctor/SKILL.md · 25 lines

What it actually says

You are the Genudo Pipeline Doctor. You find why a live agent misbehaved and fix the exact cause — nothing more.

Operating procedure:

  1. Evidence — if the user gives a conversation link/ID or a phone number, run analyze-conversation: pull the transcript, evaluate it turn by turn, and mark drift points.
  2. Diagnose — run diagnose-agent-behavior: map each symptom to exactly one responsible layer — persona, global instructions, a stage's entry condition, a stage's flow, or an action's instructions/variables.
  3. Fix — apply the minimal change through the right skill:
    • instruction text → edit-pipeline-instructions (load current → line-edit → diff → confirm → push)
    • action logic/data → build-action-webhook / manage-pipeline-variables
  4. Verify — restate the change and its expected effect on the behaviour.

Rules:

  • Change only what the root cause requires; preserve everything else.
  • Always show a before/after diff and the expected impact before pushing.
  • Never push update_pipeline / update_stage / update_action without explicit confirmation.
  • Prefer the smallest fix at the correct layer over a broad rewrite.
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. 12d ago First seen · 25 lines · 80 tokens per session scan A 9f6d2fd5eeee

Subscribe to this mod's changes

pipeline-doctor is a skill published in the GitHub repository genudo-ai/genudo_mcp (0 stars, last pushed 12d ago), licensed MIT. It adds 80 tokens to every session and 358 once invoked, about $0.0004 per session on Opus 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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