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 agentmods add skills/grcengineering/companion/progress-trackernpx skills add grcengineering/companion --skill progress-trackergit clone --depth 1 https://github.com/grcengineering/companionWhat 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 | $0.00055 | $0.00482 |
| Opus 5 | $0.00028 | $0.00241 |
| Sonnet 5 | $0.00011 | $0.00096 |
| Haiku 4.5 | $0.00006 | $0.00048 |
Grade A, and why
progress-tracker 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 2d 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.
What it actually says
progress-tracker
What
Track concepts the learner has not covered, touched, practised, or internalised. Tier 0 stores anonymous progress in browser localStorage; cross-device progress requires a future signed-in backend.
When
- The learner asks what they have learned.
- The learner asks what to revisit.
- A quiz, lab, scenario, or reflection creates progress signal.
- The Companion needs to schedule a spaced review.
Not For
- Scoring the learner's organization, programme, or maturity.
- Updating learner identity or goals. Use
profile-refresher. - Teaching or quizzing by itself unless paired with
recall-quiz.
Inputs
- Current concept list.
- Recent learner answers, artefacts, or reflection notes.
- Existing local progress state, if available.
Steps
- Identify the concept or skill being updated.
- Classify state as not covered, touched, practised, or internalised.
- Explain the evidence for the classification in one sentence.
- Suggest one next rep.
- Add or propose a spaced review prompt.
Validation
- Progress state is based on observable learning signal.
- No programme maturity or job performance score is implied.
- The next rep is specific.
Gotchas
- Do not equate confidence with mastery; require retrieval, practice, or transfer evidence.
- If there is no durable storage, return a copyable progress note.
- If the learner asks "am I ready to run this at work?", convert to learning readiness.
Failure Modes
- False precision: use coarse states, not percentages.
- Operational scoring: track learning only.
- Stale state: propose review rather than assuming internalisation.
Examples
- User asks "What should I revisit?" -> List touched-but-not-practised concepts and recommend one recall prompt.
- After a correct explain-back -> Move the concept from practised toward internalised with a review date.
- User asks "Is my programme mature?" -> Refuse maturity scoring and offer a learning progress check instead.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 62 lines · 55 tokens per session scan A ab5cfbe458dc
progress-tracker is a skill published in the GitHub repository grcengineering/companion (32 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 482 once invoked, about $0.0003 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 2026-08-30.
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