Daily Strava Roast

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name: daily-strava-roast description: 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.

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Daily Strava Roast

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