analyse

analyse is a command for coding agents from airbone42/360-data-athlete. It costs 0 tokens per session (1,866 once invoked), scanned A, original, MIT.

A command for reviewing a completed training session using activity data from intervals.icu, a service for recording and analysing workouts.

In plain words
What is it for?
Use it to check completion, repetitions, cadence, heart rate, and perceived effort against a training plan.
Why use it?
It compares the session with the planned workout and avoids treating a smart trainer's automatically controlled power as proof of an athlete's performance.

Command

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the aicoach-framework plugin — 7 commands, 16 agents shipped together

Install

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.

agentmods
npx agentmods add commands/airbone42/360-data-athlete/analyse
Clone the repo
git clone --depth 1 https://github.com/airbone42/360-data-athlete

Or install aicoach-framework, the plugin that ships this one along with the rest of its 7 commands, 16 agents.

Wrote 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.

agentmods badge for analyse

README.md
[![agentmods](https://agentmods.dev/badge/commands/airbone42/360-data-athlete/analyse.svg)](https://agentmods.dev/commands/airbone42/360-data-athlete/analyse)
Your own site
<a href="https://agentmods.dev/commands/airbone42/360-data-athlete/analyse"><img src="https://agentmods.dev/badge/commands/airbone42/360-data-athlete/analyse.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01866
Opus 5 $0.00000 $0.00933
Sonnet 5 $0.00000 $0.00373
Haiku 4.5 $0.00000 $0.00187

Measured 4d ago against content hash 5f285c303361, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyse 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 4d 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.

commands/analyse.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/analyse — Activity analysis

Analyse a completed training session.

Arguments

$ARGUMENTS Required: intervals.icu activity ID, e.g. i12345678


Workflow

Analysis standard (MANDATORY):

  • FIT file + sub-laps is the primary data path — intervals.icu streams alone are not enough
  • Compliance — one canonical definition: direct compliance = actual vs. planned, computed by the analysing agent itself from activity + plan data. The precomputed compliance property from intervals.icu is unreliable — it is never cited and never used as a gate; coaching feedback never comments on it
  • ERG-trainer power is not an athlete signal (MANDATORY). On an ERG-controlled smart trainer the device holds target watts whatever the athlete is doing, so a flat power trace is the trainer working, not the rider. Never report "power held to the last rep", "zero decay", "watts never dropped" as a strength, a finding, or evidence of adaptation, and never gate a progression on it. What stays valid from such a session is repetition count (volume compliance), cadence, HR and RPE — cadence being the variable that actually carries muscular capacity, since it falls when the athlete runs out while power does not. Check config/equipment.md for the trainer and its control mode before analysing any indoor ride; where the mode is unknown, assume ERG for a structured session and state the assumption. Prescribed watt anchors remain valid as dose — only the inference from held watts back to athlete state is invalid.
  • GCT on recovery runs: High GCT during slow jogging is biomechanics, not error. Only evaluate GCT as a fatigue indicator when the GCT rise disproportionately exceeds the pace slowdown (pace-normalized). Do not comment negatively on absolute GCT values in recovery phases.
  • Cool-down running dynamics are out of scope (MANDATORY). The cool-down is run at a shuffle — far below any pace the athlete trains at — and gait at that speed is a different movement pattern, not a slower version of the same one. Ground-contact time, vertical oscillation, step length, cadence and contact balance measured there describe the shuffle, not the session. Restrict every running-dynamics statement, trend and fresh-vs-fatigued comparison to the warm-up- completed main block; never close a dynamics argument with a cool-down value, and never let a claim about persistence ("the shift had not recovered by the end") rest on cool-down data. State the excluded window rather than silently trimming it. The same applies to the post-interval jog segments inside a session.

Read the full file on GitHub · 184 lines

Changes

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.

  1. 4d ago First seen · 184 lines · 0 tokens per session scan A 5f285c303361

Subscribe to this mod's changes

analyse is a command published in the GitHub repository airbone42/360-data-athlete (22 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,866 tokens. 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.