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 ZachBeta/claude-as-coach --skill retrospective-alice-personalgit clone --depth 1 https://github.com/ZachBeta/claude-as-coachWrote 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/zachbeta/claude-as-coach/retrospective-alice-personal)<a href="https://agentmods.dev/skills/zachbeta/claude-as-coach/retrospective-alice-personal"><img src="https://agentmods.dev/badge/skills/zachbeta/claude-as-coach/retrospective-alice-personal/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/zachbeta/claude-as-coach/retrospective-alice-personal"><img src="https://agentmods.dev/badge/skills/zachbeta/claude-as-coach/retrospective-alice-personal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00023 | $0.01044 |
| Opus 5 | $0.00012 | $0.00522 |
| Sonnet 5 | $0.00005 | $0.00209 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
retrospective-alice-personal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Retrospective - Personal Extensions (Running Training Example)
This skill extends retrospective-base with running training-specific context.
Note: This is an EXAMPLE showing how to adapt the retrospective framework for couch-to-5K training. Replace with your own domain terminology.
Personal Configuration
Timezone
TZ='America/New_York' date '+%A, %B %d, %Y - %I:%M %p %Z'
# Show week being reviewed (includes previous Sunday)
for day in 9 10 11 12 13 14 15; do
TZ='America/New_York' date -d "2025-11-$day" '+%A, November %d, 2025'
done
Domain-Specific Terminology
Context Line
Training Context: Brief context about training phase or race schedule (e.g., "Week 4 of couch-to-5K, building endurance")
Training States
When describing capacity/progress trends, use these training-specific modes:
- Base building: Establishing aerobic foundation, focus on consistency and time on feet
- Build phase: Increasing volume/intensity, testing boundaries carefully
- Taper/recovery: Reducing load before race or after hard block
- Maintenance: Holding current fitness level, not actively building
- Comeback/rebuild: Building back after injury or break
Running-Specific Patterns
When identifying patterns in "What Worked" or "What Didn't Work":
- Training execution (completed runs, hit paces, followed plan)
- Pace/distance/time progressions
- Heart rate zone distribution (too much Z3/Z4, good Z2 base)
- Running form and efficiency
- Fueling and hydration strategies
- Recovery quality (sleep, soreness, freshness)
- Injury prevention (stretching, strength work, rest days)
Experiment Types
Common experiments in running context:
- Pacing strategies (testing different effort levels, negative splits)
- Fueling trials (pre-run meals, during-run nutrition, hydration)
- Training plan modifications (run/walk ratios, frequency, volume)
- Recovery strategies (ice baths, foam rolling, active recovery runs)
- Gear testing (shoes, clothing, accessories)
- Form adjustments (cadence, foot strike, posture)
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.
- 12d ago First seen · 129 lines · 23 tokens per session scan A 5b38ff159a5a
retrospective-alice-personal is a skill published in the GitHub repository ZachBeta/claude-as-coach (5 stars, last pushed 7mo ago), licensed MIT. It adds 23 tokens to every session and 1,044 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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