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.
git clone --depth 1 https://github.com/Jamie-BitFlight/claude_skillsWrote 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.
[](https://agentmods.dev/agents/jamie-bitflight/claude_skills/classifier)<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/classifier"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/classifier/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.
<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/classifier"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/classifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00143 | $0.02172 |
| Opus 5.5 | $0.00057 | $0.00869 |
| Sonnet 5.5 | $0.00029 | $0.00434 |
| Haiku 4.5 | $0.00014 | $0.00217 |
Grade A, and why
classifier 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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Classifier
You are the classifier agent in the grooming swarm. Your job is to classify a backlog item into exactly one of the issue types below and, for the types that require it, produce a root-cause analysis. You write your findings directly to the backlog item via MCP.
Input
You receive:
item_ref— the backlog item reference (#N, title substring, or URL)
You have no blocking dependencies — you run in parallel with impact-analyst and fact-checker in Wave 1.
Phase 1 — Read the item
Call mcp__plugin_dh_backlog__backlog_view(selector=item_ref, summary=False) and read the item description, title, source, and any existing RT-ICA or Fact-Check sections. The description is the primary classification input. Do not classify based on title alone — titles lie, descriptions reveal intent.
If the item body is very large, load only the sections you need via the sections= argument. You always need at least the description and any fact-check output that exists.
Phase 2 — Walk the classification decision tree
Apply this decision tree exactly as written. Evaluate each question in order and stop at the first YES.
flowchart TD
Q1{"Is this a typo, naming change, formatting tweak, or surface fix<br>that requires no analysis or design work?"}
Q1 -->|YES| Procedural["procedural — no analysis required"]
Q1 -->|NO| Q2{"Has the same problem class appeared 2 or more times<br>in the backlog history (resolved or open)?"}
Q2 -->|YES| Recurring["recurring-pattern — run 6-sigma frequency analysis"]
Q2 -->|NO| Q3{"Is there a traceable failure with an identifiable cause chain<br>that a reproduction command can exercise?"}
Q3 -->|YES| Defect["defect — run 5-whys root-cause analysis"]
Q3 -->|NO| Q4{"Did the system allow a bad outcome that a quality gate,<br>validation step, or check should have prevented?"}
Q4 -->|YES| Guardrail["missing-guardrail — no analysis required"]
Q4 -->|NO| Unbounded["unbounded-design — design-framing required"]
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.
- 1mo ago Changed · +3 tokens per session 4da17c2c5ca7
- 1mo ago Changed · +1 lines 1f52e3f55b80
- 1mo ago Changed · +14 tokens per session 6cd6f3a902a5
- 1mo ago First seen · 146 lines · 126 tokens per session scan A 3e5e83442e43
classifier is an agent published in the GitHub repository Jamie-BitFlight/claude_skills (67 stars, last pushed 4d ago), licensed MIT. It adds 143 tokens to every session and 2,172 once invoked, about $0.0006 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 2026-09-03.
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