Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsnpx agentmods add skills/d-o-hub/github-template-ai-agents/intent-classifierWrote 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/skills/d-o-hub/github-template-ai-agents/intent-classifier)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/intent-classifier"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/intent-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/skills/d-o-hub/github-template-ai-agents/intent-classifier"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/intent-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 | $0.00082 | $0.00997 |
| Opus 5.5 | $0.00033 | $0.00399 |
| Sonnet 5.5 | $0.00016 | $0.00199 |
| Haiku 4.5 | $0.00008 | $0.00100 |
Grade A, and why
intent-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 24d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent Classifier
Classify user requests and route them to the most appropriate skill, command, or specialized agent.
When to Use
- User asks which skill to use or how to route a request
- Need to determine which skill handles a given task
- Multiple skills could handle a request and disambiguation is needed
- Even if they just say "which skill should I use" or "route this"
Classification Workflow
1. Intent Extraction
- Parse the user's natural language request
- Identify primary action (create, update, delete, analyze, etc.)
- Extract entities (file paths, technologies, specific terms)
2. Skill Matching
- Compare against available skills catalog
- Score match confidence for each candidate
- Consider skill descriptions and keywords
3. Route Decision
- Select highest-confidence match
- Handle ties and ambiguous cases
- Fall back to general assistance if no match
Classification Rules
Priority Order
- Exact keyword match - Skill description contains exact phrase
- Domain match - Technology stack alignment
- Action match - Verb/action alignment
- Context match - File paths, extensions, surrounding context
Confidence Scoring
High (0.8-1.0): Exact description match, multiple keyword hits
Medium (0.5-0.7): Partial match, related domain
Low (0.3-0.4): Weak match, shared keywords only
None (<0.3): No relevant match
Multi-Intent Handling
When a request contains multiple intents:
- Sequential - Chain skills in dependency order
- Parallel - Execute independent skills simultaneously
- Composite - Use parent skill that orchestrates sub-skills
Fallback Strategies
| Confidence | Action |
|---|---|
| > 0.7 | Execute primary skill |
| 0.5 - 0.7 | Execute skill with confirmation |
| 0.3 - 0.5 | Present top 2-3 options to user |
| < 0.3 | Use general assistance |
Dynamic Catalog
Update the skill catalog using:
./scripts/generate-skill-catalog.sh
What ships with it
5 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.
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.
- 24d ago Changed · +2 lines efa79305bd29
- 1mo ago First seen · 125 lines · 82 tokens per session scan A 6a2d4cfb7bcf
intent-classifier is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 82 tokens to every session and 997 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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