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BC intervals-icu-api

Complete guide for accessing and managing training data with the intervals.icu API. Use when working with Intervals.icu athlete profiles, activities, workouts, events, wellness data, and training plans. Covers authentication, retrieving activities with combined data fields, managing calendar events with planned workouts, and creating/updating training data. Includes curl examples for all major operations.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 5 575 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Complete guide for accessing and managing training data with the intervals.icu API. Use when working with Intervals.icu athlete profiles, activities…

As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

IntegrationData and analyticsPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
80
Quality 40%
77
Run on models
none yet
Process rating
C
52/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • medium Exfiltration net-credential-use SKILL.md:595
    Credential used in a network call (verify the destination is the intended service)
    ACTIVITIES=$(curl -s -H "Authorization: ApiKey $ATHLETE_ID:$API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:599
    Credential used in a network call (verify the destination is the intended service)
    EVENTS=$(curl -s -H "Authorization: ApiKey $ATHLETE_ID:$API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:603
    Credential used in a network call (verify the destination is the intended service)
    WELLNESS=$(curl -s -H "Authorization: ApiKey $ATHLETE_ID:$API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:682
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "Authorization: ApiKey $ATHLETE_ID:$API_KEY" \

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5575 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 52/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5575 tokens
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 11 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 408: enough signal without eating the budget
  • +4Structure: 46 headings
  • +3Step-by-step instructions: 9 items
  • +3Output format is stated explicitly
  • +4Has examples (25 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.