chain-instrumentation-debug

chain-instrumentation-debug is a skill for Claude Code, Codex from LiuYihey/Agent-Engineering. It costs 50 tokens per session (1,256 once invoked), scanned A, original, MIT.

A debugging method that adds logs at each important step in a request and response, from a user action through the server and database back to the screen.

In plain words
What is it for?
Use it for reproducible full-stack bugs, inconsistent behavior, state that silently reverts, race conditions, or interfaces that do not match server data.
Why use it?
It shows where a value changes, disappears, or becomes incorrect when reading the code alone is not enough.

Skill for Claude CodeCodex

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

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.

agentmods
npx agentmods add skills/liuyihey/agent-engineering/chain-instrumentation-debug
Any agent
npx skills add LiuYihey/Agent-Engineering --skill chain-instrumentation-debug
Clone the repo
git clone --depth 1 https://github.com/LiuYihey/Agent-Engineering

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 chain-instrumentation-debug

README.md
[![agentmods](https://agentmods.dev/badge/skills/liuyihey/agent-engineering/chain-instrumentation-debug.svg)](https://agentmods.dev/skills/liuyihey/agent-engineering/chain-instrumentation-debug)
Your own site
<a href="https://agentmods.dev/skills/liuyihey/agent-engineering/chain-instrumentation-debug"><img src="https://agentmods.dev/badge/skills/liuyihey/agent-engineering/chain-instrumentation-debug.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,256 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00050 $0.01256
Opus 5 $0.00025 $0.00628
Sonnet 5 $0.00010 $0.00251
Haiku 4.5 $0.00005 $0.00126

Measured 5d ago against content hash 549f60194f25, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

chain-instrumentation-debug 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 5d 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/chain-instrumentation-debug/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Chain Instrumentation Debugging

A systematic methodology for diagnosing full-stack bugs by instrumenting the data flow with console output at critical transition points, then reading the logs to pinpoint exactly where state diverges from expectations.

When to Invoke

  • Bug is reproducible but root cause is unclear from code reading
  • User reports inconsistent behavior ("sometimes works, sometimes doesn't")
  • UI doesn't reflect server state, or vice versa
  • State appears to revert silently after an action
  • Race conditions or timing-related bugs
  • "Works on refresh but not on first interaction"
  • Any bug where you need to understand the actual runtime data flow vs. the expected flow

Methodology

Step 1: Map the Data Flow

Before writing any logs, trace the complete request/response chain on paper:

User Action → Client Handler → Optimistic Update (set) → API Call →
Server Endpoint → DB Mutation → Response Serialization →
Client Response Handler → State Reconciliation (applyState) → UI Re-render

Identify every point where a value could change or be lost.

Step 2: Insert Instrumentation at Every Transition

Add console.log at every state transition in the chain. Use a consistent prefix tag so logs can be filtered.

Client-side action (example pattern):

myAction: (id) => {
  console.log('[myAction] start, input:', id, 'current state:', get().myField)
  
  // Optimistic update
  set({ myField: newValue })
  console.log('[myAction] after optimistic set, myField:', get().myField)
  
  // API call
  api.myAction(id).then((response) => {
    console.log('[myAction] API response, myField:', response.myField, 'other:', response.otherField)
    
    // State reconciliation
    applyState(response)
    console.log('[myAction] after applyState, myField:', get().myField)
  }).catch((err) => {
    console.error('[myAction] failed:', err)
  })
},

Server-side endpoint (example pattern):

app.post('/api/myAction', (req, res) => {
  const session = getSession(req.cookies.sid)!
  console.log('[endpoint] request received, session field:', session.myField)
  
  doMutation(session.id, req.body.value)
  console.log('[endpoint] after mutation, session field (in-memory):', session.myField)
  
  const fresh = getSession(req.cookies.sid)!
  console.log('[endpoint] fresh from DB, session field:', fresh.myField)
  
  res.json(buildState(fresh))
})

Read the full file on GitHub · 135 lines

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. 5d ago First seen · 135 lines · 50 tokens per session scan A 549f60194f25

Subscribe to this mod's changes

chain-instrumentation-debug is a skill published in the GitHub repository LiuYihey/Agent-Engineering (5 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 1,256 once invoked, about $0.0003 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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