Daily Strava Roast

Generate a playful or sharp daily roast of recent Strava activity. Use when asked to roast, recap, tease, or humorously summarize a Strava workout or a recent day of training. Useful for scheduled daily activity roasts, playful fitness summaries, or lightly sarcastic post-workout commentary. Prefer the deterministic package/script for data prep and fallback; when running inside OpenClaw, use the connected/default runtime model only for the final paragraph if available, then fall back to the deterministic roast path on failure.

Use this skill to turn recent Strava activity into a short roast-style summary.

Default workflow

1. Use the deterministic implementation first to fetch and summarize activity.
2. If you are inside OpenClaw and want the V2 path, use the structured context/prompt output as model input for the final paragraph only.
3. If connected-model generation is unavailable or weak, fall back to the deterministic roast output.
4. Do not pretend the standalone Python package has a built-in OpenClaw connected-model API if it does not.

What this skill does

This skill provides:

• deterministic Strava fetch + summary tooling
• adjustable tones and spice levels
• V1 roast fallback that is stable and testable
• V2 context/prompt building for better final-paragraph generation in the OpenClaw runtime

Preferred commands

Use the packaged CLI for deterministic preparation and fallback:

uv run --project {baseDir} daily-strava-roast summary --json --pretty
uv run --project {baseDir} daily-strava-roast context --pretty
uv run --project {baseDir} daily-strava-roast prompt
uv run --project {baseDir} daily-strava-roast roast

Do not rely on the removed legacy script path. Use the packaged CLI commands only.

Runtime guidance

When invoked inside OpenClaw for an actual roast reply:

• run deterministic preparation first
• use the connected/default runtime model only to write the final roast paragraph
• keep that paragraph to one short paragraph
• do not invent stats
• if generation fails, return the deterministic roast instead of erroring

Runtime recipe

Use this sequence:

1. Build context JSON:

uv run --project {baseDir} daily-strava-roast context --pretty

2. Build the constrained prompt:

uv run --project {baseDir} daily-strava-roast prompt

3. Ask the connected/default OpenClaw runtime model to write the final paragraph from that prompt.
4. Before replying, sanity-check the generated paragraph:
   • exactly one paragraph
   • one or two sentences max unless unusually short
   • no bullet points
   • no invented stats
   • no stat dump; usually no more than two concrete metrics unless a third really earns its place
   • not generic AI filler
   • avoids banned phrases, stale identity/relationship jokes, pet phrases, and over-clever wording
   • avoids poetic or cosmic phrasing
   • tone matches requested spice/tone closely enough
5. If the paragraph fails those checks or generation is unavailable, fall back to:

uv run --project {baseDir} daily-strava-roast roast

Fallback triggers

Fall back immediately if any of these happen:

• no connected/default runtime model is available
• generated output is empty
• generated output invents numbers, activities, or claims not present in the prompt/context
• generated output is multiple paragraphs or list-like
• generated output crams in too many stats without real comedic payoff
• generated output uses banned phrases or obvious close variants
• generated output leans on stale identity, relationship, or defining-trait jokes
• generated output leans on polished LLM-clever wording instead of dry mockery
• generated output drifts into poetic, cosmic, or overly ornate phrasing
• generated output is obviously generic, repetitive, or less readable than the deterministic roast

When falling back:

• do not apologize unless the user needs to know
• just return the deterministic roast text

When working purely from the repo/CLI:

• treat connected-model generation as a runtime concern, not a packaged-CLI feature
• keep the deterministic path working without extra runtime dependencies

Inputs

By default the skill reads Strava app config from:

~/.openclaw/secure/strava_app.json

And by default the token file is:

~/.openclaw/workspace/agents/tars-fit/strava_tokens.json

Normal auth behaviour:

• treat ~/.openclaw/secure/strava_app.json as the canonical app-credentials source
• if setup already exists, expired access tokens should refresh automatically using the refresh token
• if Strava still returns 401, retry once after a forced refresh
• if the token file is missing, invalid, or missing required fields, treat that as initial setup required and tell the user clearly
• if the token file exists but app credentials are missing or incomplete, return config_incomplete clearly
• if setup exists but refresh/reauthorisation is needed, return the reauth-required path instead of pretending it is a rest day
• avoid depending on sourced shell profiles for routine auth

Use this to inspect auth readiness:

uv run --project {baseDir} daily-strava-roast auth-url

Use JSON mode when another agent needs machine-readable status:

uv run --project {baseDir} daily-strava-roast roast --json --pretty

Tones

Supported tones:

• dry
• playful
• savage
• coach

Spice

Spice controls roast intensity:

• 0 — gentle
• 1 — light tease
• 2 — proper roast
• 3 — scorched earth

References

Read as needed:

• references/design.md for roast heuristics and failure cases
• docs/V2.md for the V2 architecture and package/runtime boundary