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 avmnu-sng/sutra --skill effort-calibrationgit clone --depth 1 https://github.com/avmnu-sng/sutraWrote 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/avmnu-sng/sutra/effort-calibration)<a href="https://agentmods.dev/skills/avmnu-sng/sutra/effort-calibration"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/effort-calibration/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/avmnu-sng/sutra/effort-calibration"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/effort-calibration.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 | $0.00041 | $0.01488 |
| Opus 5 | $0.00020 | $0.00744 |
| Sonnet 5 | $0.00008 | $0.00298 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
effort-calibration 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 10d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effort calibration
Energy is finite and every task asks for a share of it: tokens, parallel agents, verification passes, independent attempts, artifacts. Spend too little on a high-stakes change and you ship a defect; spend a fortune on a typo and you burn the budget the real work needed. Match the spend to the task -- and never buy the savings with correctness.
The two dials
Two independent properties set the budget. Do not collapse them into one.
- Complexity sets the breadth budget -- how many agents you fan out, how many independent attempts you make, how many artifacts you produce, how wide you cast for coverage. More unknowns and moving parts earn more breadth.
- Blast radius sets the correctness floor -- which verification is mandatory and non-negotiable. How far a wrong answer reaches earns a higher floor, regardless of how simple the diff looks.
You trade away breadth to save energy. You never trade away the floor.
Classify in four questions
- Stakes. Does the change hit an irreversible or public surface -- a release, a data migration, a deletion, auth or a secret, money, or a cross-component invariant? Any yes forces a T3 floor, whatever the diff size.
- Reach. Does it touch shared or core code beyond the paths you own?
- Knowns. Are the location and the shape of a correct answer already known before you start?
- Unknowns. After one read, how many independent unknowns remain -- none, a few, or many?
Map: the stakes answer sets the floor tier; reach and unknowns set the breadth
tier; the depth you run is max(floor, breadth). The floor is never lowered to
match the breadth.
The tiers
| Tier | Depth | Verification | Attempts | Artifacts | Retry / replan |
|---|---|---|---|---|---|
| T0 -- trivial, contained | Solo inline, no delegation | The change's own check, one pass | 1 | None -- answer in place | 1 replan; a second miss means you misclassified -- escalate |
| T1 -- standard, localized | Solo; delegate only mechanical legwork to one helper | Single pass, run the real path | 1 | Change plus its test | 2 attempts, 1 replan |
| T2 -- complex or shared | Fan out parallel reads and traces; keep design and trade-offs yourself; one reviewer who did not build it | Adversarial review by a different agent; single verifier | 1 plus review; two independent attempts only if the approach is genuinely uncertain | Change, test, and a short design note if a decision is load-bearing | 3 attempts, 2 replans; front-load disambiguation before building |
| T3 -- critical, irreversible | Fan out a workflow; separate builder, adversarial reviewer, and independent completeness validator -- never the same agent | Adversarial multi-vote (two or more independent reviewers, contradictions reconciled) plus an independent gate that re-runs the acceptance checks | 2-3 independent attempts on the uncertain core; choose by evidence, not confidence | Design doc or ledger, tests, an integration/topology slice, a deferred-items ledger | Bounded but every replan logged; human sign-off at the consensus gate |
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.
- 10d ago First seen · 107 lines · 41 tokens per session scan A d058435265b8
effort-calibration is a skill published in the GitHub repository avmnu-sng/sutra (2 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 1,488 once invoked, about $0.0002 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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