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 agentmods add skills/shawnla90/recursive-drift/agent-routingnpx skills add shawnla90/recursive-drift --skill agent-routinggit clone --depth 1 https://github.com/shawnla90/recursive-driftWrote 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/shawnla90/recursive-drift/agent-routing)<a href="https://agentmods.dev/skills/shawnla90/recursive-drift/agent-routing"><img src="https://agentmods.dev/badge/skills/shawnla90/recursive-drift/agent-routing.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.01685 |
| Opus 5 | $0.00018 | $0.00843 |
| Sonnet 5 | $0.00007 | $0.00337 |
| Haiku 4.5 | $0.00004 | $0.00169 |
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 6d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Routing -- Choose the Right Execution Pattern
Before spinning up agents or teams, run this decision framework. The goal is to match the execution pattern to the task, not default to the most complex option.
Step 0: Decision-Lock Check
Before analyzing execution pattern, check for an existing CONTEXT.md:
-
CONTEXT.md exists in the feature working directory -- Read the
## Decisionssection. Use locked decisions to inform the 5-dimension analysis below. Do not re-ask anything already decided. -
No CONTEXT.md AND task is complex (3+ files across 2+ concerns) -- Recommend
/discussfirst:This task touches [N] files across [concerns]. Recommend running
/discussto lock decisions before routing.If the user says "skip" or "just go", proceed to Step 1 without a CONTEXT.md.
-
Task is small (1-2 files, single concern) -- Skip directly to Step 1. No discussion needed.
Step 1: Task Analysis
Evaluate the task against these 5 dimensions. Be honest -- do not inflate complexity to justify a team.
1. File Count
How many files will be WRITTEN or EDITED (not read)?
- 1-2 files: Single session territory
- 3-4 files: Subagent territory
- 5+ files across different concerns: Team territory
2. Concern Separation
Are the outputs independent or do they need coordination?
- All outputs go in the same file or closely related files: Single session
- Outputs are in different files but follow the same pattern: Subagents (each mirrors a known pattern independently)
- Outputs are in different files AND require different expertise (content vs code vs config vs deploy): Team
3. Handoff Requirement
Does any task need the OUTPUT of another task before it can start?
- No handoffs -- all tasks can run with existing context: Subagents
- Linear handoff -- A feeds B feeds C: Single session (sequential in one context is faster than agent-to-agent messaging)
- Fan-out handoff -- A feeds B, C, D simultaneously: Team (A completes, then B/C/D run in parallel)
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.
- 6d ago First seen · 159 lines · 37 tokens per session scan A ddb4d995ea70
agent-routing is a skill published in the GitHub repository shawnla90/recursive-drift (18 stars, last pushed 5mo ago), licensed MIT. It adds 37 tokens to every session and 1,685 once invoked, about $0.0002 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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