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 makifbaysal/tasktrooper --skill performance-awarenessgit clone --depth 1 https://github.com/makifbaysal/tasktrooperWrote 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/makifbaysal/tasktrooper/performance-awareness)<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/performance-awareness"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/performance-awareness/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/makifbaysal/tasktrooper/performance-awareness"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/performance-awareness.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 | $0.00037 | $0.00921 |
| Opus 5.5 | $0.00015 | $0.00368 |
| Sonnet 5.5 | $0.00007 | $0.00184 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
performance-awareness 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Awareness
Overview
Every agent carries a performance score (0–100, starts at 100). It is not decoration: it reflects how much rework your output causes downstream, and your run context already injects it (agent.score_context) — this skill explains what moves it. A task that sails through its gates clean protects your score; one that bounces back at any gate costs you. The score rewards getting it right the first time.
Core principle: The cheapest revision is the one that never happens. Every gate you pass clean is points kept; every bounce is points lost AND time lost.
How the score moves
| Event | Delta | Who is charged |
|---|---|---|
| Your task reaches done or released | +5 each | the assignee |
| Revision requested from code_review | −10 | the in_progress owner |
| Revision requested from ready_for_qa or in_qa | −10 | the in_progress owner |
| PM UAT fails | −5 | the in_progress and in_qa owners |
| Human UAT fails | −8 | the in_progress, in_qa and pm_uat owners |
| A human overturns your approval at the same review gate (review escape) | −10 | the reviewer who approved it |
| QA: a bug it caught | +6 | QA, per bug |
| QA: a scenario it confirmed valid / invalid | +1 / −1 | QA, per scenario |
| QA: finished testing a task | +5 | QA |
| PM: completed a UAT | +5 | PM |
The asymmetry is deliberate: one revision (−10) wipes out two clean releases (+10), and Human UAT failing (−8) costs more than PM UAT failing (−5) because it escaped every earlier gate.
The gates your work passes
in_progress → code_review → ready_for_qa → in_qa → pm_uat → human_uat → done → released
(architect) (QA) (PM) (human)
A defect caught at code_review costs the developer −10. The SAME defect that slips to in_qa, pm_uat or human_uat still costs the developer and now also charges whoever owned the column it escaped through, plus the time of every role between. Catch your own defects before handoff — that is what the score is measuring.
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 · 63 lines · 37 tokens per session scan A 4b3086e093d2
performance-awareness is a skill published in the GitHub repository makifbaysal/tasktrooper (113 stars, last pushed yesterday), licensed Apache-2.0. It adds 37 tokens to every session and 921 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-05.
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Use this skill to systematically review code changes for correctness, security, performance, maintainability, and test coverage. Activates after implementation, before merging, or when asked to review a pull request or code change. Produces a structured review report with findings categorized by severity.
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