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.
npx skills add oaustegard/claude-skills --skill agent-routinggit clone --depth 1 https://github.com/oaustegard/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/skills/oaustegard/claude-skills/agent-routing)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/agent-routing"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/agent-routing/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/oaustegard/claude-skills/agent-routing"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/agent-routing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Output Handling · line 244 Model output is used without validation or sanitization. Unvalidated output injected into downstream contexts (SQL, shell, HTML) enables injection attacks and arbitrary code execution.Fix: Validate and sanitize all model output before using it in downstream contexts. Use parameterized queries for SQL, shell quoting for commands, and HTML encoding for web output.
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 | $0.00188 | $0.04974 |
| Opus 5 | $0.00094 | $0.02487 |
| Sonnet 5 | $0.00038 | $0.00995 |
| Haiku 4.5 | $0.00019 | $0.00497 |
Grade A, and why
agent-routing 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 7d 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 — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Routing — model, effort, and cascade selection
The rule that decides everything
Cost is output tokens × output price. Prices span ~5× across tiers. Token counts span up to 7× within a single tier depending on task shape. The shape therefore decides more than the tier does, and routing on the per-token discount gets the answer backwards.
Measured 2026-08-17, 14 spec-dense Python modules graded by hidden tests, all tiers at equal quality where noted:
| arm | tok/task | pass | $/task | vs opus |
|---|---|---|---|---|
| haiku-solo | 20,051 | 14/14 | $0.1007 | 1.30× |
| haiku + concision | 13,342 | 12/14 | $0.0672 | 1.01× |
| opus-solo | 3,001 | 14/14 | $0.0774 | 1.00× |
| sonnet-base | 4,687 | 14/14 | $0.0478 | 0.62× |
| sonnet + concision | 2,951 | 13/14 | $0.0305 | 0.42× |
| sonnet cascade (below) | — | 14/14 | $0.0315 | 0.41× |
Haiku is 5× cheaper per token and cost 30% more per solved task than Opus, because it emitted 6.7× the tokens. Prices: Haiku 4.5 $1/$5, Sonnet 5 $2/$10, Opus 5 $5/$25 per MTok.
Two questions before spawning
- Is the output short or long? Short = a schema instance, a label, an answer, a small patch. Long = a module, a document, a plan, a review.
- Is it mechanically checkable, or does it need judgment?
| short output | long output | |
|---|---|---|
| checkable | haiku @ low + verifier |
sonnet @ medium + concision + verifier |
| judgment | sonnet @ medium |
sonnet/opus @ high |
Output length is the discriminator because it is what the verbosity multiplier multiplies. Haiku's premium is invisible on a 200-token JSON object and ruinous on a 700-token module that costs it 13,000 tokens of thinking to produce.
Routing table
| Task shape | Model | Effort | Verify with |
|---|---|---|---|
| Extraction, classification, format transforms, schema-bound output | haiku |
low |
schema / spot-check |
| Closed-form computation, state tracking, multi-hop lookup | haiku |
low |
deterministic check |
| Constraint-bound generation (exact counts, required tokens, lipograms) | haiku |
low |
mechanical checker |
| Bulk scans/greps, per-file summaries, fan-out reads | haiku |
low |
sample audit |
| Code generation from a spec; any long structured artifact | sonnet |
medium |
run the tests |
| Code edits with tests available | sonnet |
medium |
run the tests |
| Judging / scoring another model's output | sonnet+ |
medium |
— (judge ≠ worker) |
| Ambiguity resolution, novel synthesis, architecture, taste | sonnet/opus |
high |
human or panel |
| Long-horizon multi-step agentic work, cross-file reasoning | sonnet/opus |
high/xhigh |
milestone checks |
What ships with it
4 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.
- 7d ago Changed · +47 lines · +19 tokens per session c79a17c2dfa3
- 12d ago First seen · 275 lines · 169 tokens per session scan A 8d6e979ed69c
agent-routing is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed yesterday), licensed MIT. It adds 188 tokens to every session and 4,974 once invoked, about $0.0009 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 2026-08-30.
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