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 rlacombe/switchback-running --skill nutritiongit clone --depth 1 https://github.com/rlacombe/switchback-runningWrote 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/rlacombe/switchback-running/nutrition)<a href="https://agentmods.dev/skills/rlacombe/switchback-running/nutrition"><img src="https://agentmods.dev/badge/skills/rlacombe/switchback-running/nutrition/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/rlacombe/switchback-running/nutrition"><img src="https://agentmods.dev/badge/skills/rlacombe/switchback-running/nutrition.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00010 | $0.00265 |
| Opus 5.5 | $0.00004 | $0.00106 |
| Sonnet 5.5 | $0.00002 | $0.00053 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
nutrition 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.
What it actually says
Nutrition and Hydration
Minimum evidence
Read profile, health constraints, event or workout duration and intensity, weather, elevation, carrying capacity, prior intake, tolerance, and rehearsals. Retrieve the relevant activity when reviewing execution.
Use get_events for the planned effort, get_activity or
get_strava_activity for completed execution, and get_weather with profile
coordinates when conditions matter. Use streams only for a defined analysis.
Knowledge
Read knowledge/nutrition.md and environmental guidance when conditions matter.
Distinguish research-supported ranges from coaching heuristics and product labels.
Analysis
Calculate carbohydrates, fluid, sodium, caffeine, and calories in consistent units. Compare hourly intake with duration, conditions, athlete history, and what was practiced. Do not prescribe a universal target, infer sweat rate without measurement, or recommend medication. Apply health triage to confusion, rapid weight change, persistent vomiting, or other warning signs.
Output
Offer a starting range, operational plan, alternatives, and rehearsal or monitoring method. State assumptions and missing evidence. Save only accepted, athlete-specific tolerances and outcomes, not provisional explanations.
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 · -94 lines · -5 tokens per session 98ac345d7061
- 1mo ago First seen · 126 lines · 15 tokens per session scan A 3b8ab74fbffb
nutrition is a skill published in the GitHub repository rlacombe/switchback-running (10 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 265 once invoked, about $0.0000 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 2026-08-30.
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Retrieve a paper, read it, and run the full per-paper propstore ingestion flow through nested skills. Give it a URL, DOI, or title.
ai-analyzer-v2
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