Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add pitimon/8-habit-ai-dev/plugin install 8-habit-ai-devWrote 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/pitimon/8-habit-ai-dev/calibrate)<a href="https://agentmods.dev/skills/pitimon/8-habit-ai-dev/calibrate"><img src="https://agentmods.dev/badge/skills/pitimon/8-habit-ai-dev/calibrate.svg" alt="Measured on agentmods" 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 | $0.00089 | $0.01831 |
| Opus 5 | $0.00044 | $0.00915 |
| Sonnet 5 | $0.00018 | $0.00366 |
| Haiku 4.5 | $0.00009 | $0.00183 |
Grade A, and why
calibrate 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 8d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Calibrate (ปรับจูนระดับวุฒิภาวะ)
Habit: H8 — Find Your Voice | Anti-pattern: Giving identical verbose guidance to a senior engineer and a first-time user
Why This Exists
The maturity model defined in rules/effective-development.md — Dependence → Independence → Interdependence → Significance — has existed in this plugin's rules for a long time but was never operationalized. Every session treated experienced users the same as first-run users: same verbose prompts, same checkpoint ceremony, same beginner examples. This wastes experienced users' tokens and time, and reads as condescending.
/calibrate closes that gap. It runs a brief self-assessment, writes a profile file, and lets other skills adapt. No enforcement, no tracking — just a signal the user opts into that informs the guidance they receive.
Inspired by (not copied from) Hermes Agent's USER.md pattern: explicit, user-facing, and editable. We do not implement passive inference (that would need a runtime we don't have) — this is active self-assessment instead.
Process
Step 0: Check for an existing profile
Read ~/.claude/habit-profile.md. Three cases:
Case A — no profile exists: proceed to Step 1 (fresh calibration).
Case B — profile exists and is less than 90 days old: show the user their current level, calibrated date, and age in days. Ask: "Your profile says you're at [Level], calibrated [N] days ago. Re-calibrate anyway?" If no, exit with the current profile path. If yes, proceed to Step 1.
Case C — profile exists and is 90+ days old: show the user their current level and age. Say: "Your profile is [N] days old — your practice may have changed. Recommend re-calibrating." Then ask the same yes/no. Default to yes at this age.
If the argument --force is present, skip the confirmation entirely and proceed to Step 1.
Step 1: Ask the 5 core questions
Ask these five questions one at a time. Wait for each answer before asking the next. Do not paste all five at once — give the user space to think.
What ships with it
2 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.
- 8d ago First seen · 116 lines · 89 tokens per session scan A 9aadbd9b2dc5
calibrate is a skill published in the GitHub repository pitimon/8-habit-ai-dev (3 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 1,831 once invoked, about $0.0004 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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