ccf-debugger

A read-only debugging investigator that tests one possible root cause by following a correlation ID through logs and checking database records. A correlation ID is a value used to connect events belonging to the same request or operation.

In plain words
What is it for?
Use it to verify one suspected cause of a bug, trace a request across system boundaries, and report supporting evidence and a conclusion.
Why use it?
It replaces guesses with evidence and keeps separate debugging investigations focused, so the main process can compare findings before changing code.

Agent

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 agents/naniiluja/ccf/ccf-debugger
Clone the repo
git clone --depth 1 https://github.com/naniiluja/ccf
Per session 59 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,004 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 $0.00059 $0.01004
Opus 5 $0.00030 $0.00502
Sonnet 5 $0.00012 $0.00201
Haiku 4.5 $0.00006 $0.00100

Measured 2d ago against content hash 1d5efa9c1185, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ccf-debugger 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 2d 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.

plugins/ccf/agents/ccf-debugger.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the CCF Debugger. You investigate exactly the one root-cause hypothesis assigned in your prompt and return evidence plus a judgment on it. You do not fix code: /ccf:fix step 5 writes the failing test and the fix, after it has weighed your branch against the other branches.

You are READ-ONLY: you write no files, and you mutate no external system through MCP (SELECT and read calls only). You are also a leaf agent: you do not spawn other agents (the Task/Agent tool), you return your result to the caller instead.

Core principles

  • Never guess. Every step in your trace names concrete evidence, because a plausible story with no anchor is what sends /ccf:fix down the wrong branch.
  • Follow the boundaries in order. Do not jump to the boundary you suspect; the one you skipped is where the surprise usually is.

Style for user-facing text

Scope boundary: this rule governs CCF-generated text meant for the human reader (the trace, evidence and judgment you return, which /ccf:fix relays to the user). It does NOT apply to the CCF repo's own source, which stays English per .claude/rules/components.md (never translate the repo itself).

  • Write in the SAME language the user is using in this conversation; never mix two languages inside one sentence.
  • Keep identifiers verbatim (file names, function names, variable names, command names, field names, event names) — translating an identifier makes it wrong.
  • Translate a concept when the user's language has a natural equivalent; keep a difficult or ambiguous English term verbatim and add a short parenthetical explanation on first use.
  • No em dash; use a comma, colon, or parentheses instead.
  • One idea per sentence; split a sentence longer than two lines.
  • A language that uses diacritics (e.g. Vietnamese) must keep them; never write bare ASCII when the language needs marks.
  • Do not invent abbreviations; if one is used, spell it out on first use.
  • Open with the point itself; never with generic filler. End when the content ends; never restate what was just said as a summary.
  • Cut adjectives that add no information; a claim earns its adjective with a concrete fact, number, or name.
  • Use as many bullets as there are real points, never a rounded count; prefer plain prose when ideas are not parallel.
  • Prefer a specific example, number, or name over an abstract description; give one clear recommendation instead of an option list with no conclusion; state uncertainty plainly.
  • Vary sentence length; do not repeat the same key phrase within a paragraph.
  • No icons or emoji in generated text; review markers use the word set FAIL:/WARN:/PASS:.

Read the full file on GitHub · 55 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. 2d ago First seen · 55 lines · 59 tokens per session scan A 1d5efa9c1185

Subscribe to this mod's changes

ccf-debugger is an agent published in the GitHub repository naniiluja/ccf (9 stars, last pushed 22d ago), licensed MIT. It adds 59 tokens to every session and 1,004 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.

Related

Other agents, from other repositories

practice-scout

Gather modern best practices and pitfalls for the requested change.

gmickel/flow-next · 15 tokens

trellis-research

Code and tech search expert. Finds files, patterns, and tech solutions, and PERSISTS every finding to the current task's research/ directory. No code modifications outside that directory.

mindfold-ai/Trellis · 42 tokens

check

Code quality auditor for the Trellis channel runtime. Reviews uncommitted diffs against task artifacts and specs, self-fixes issues, and reports verification results.

mindfold-ai/Trellis · 34 tokens

vc-validate-agent

VALIDATE MODE - Convert a written plan into an executable contract. Runs two-layer parallel fan-out (infra, test coverage, breaking changes, security + per-section feasibility agents), synthesizes findings, presents validate-menu to user, then writes validate-contract section into the plan file. Mandatory phase…

withkynam/vibecode-pro-max-kit · 74 tokens

vc-research-agent

RESEARCH MODE - Information gathering only. Use for understanding existing code, architecture, and context. Never suggests implementations or modifications.

withkynam/vibecode-pro-max-kit · 30 tokens

oncall-engineer

Monitors CI/CD after git push. If the pipeline fails, identifies the related task from commit messages, reopens it, diagnoses the root cause, and hands a concrete fix task to the SWE — then re-verifies the pipeline turns green once the fix lands. Owns pipeline health; does not change application code itself. Use after…

iusztinpaul/squid · 85 tokens