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 agents/danielbirk04/capusqa/capusqa-testergit clone --depth 1 https://github.com/DanielBirk04/capusqaWrote 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/agents/danielbirk04/capusqa/capusqa-tester)<a href="https://agentmods.dev/agents/danielbirk04/capusqa/capusqa-tester"><img src="https://agentmods.dev/badge/agents/danielbirk04/capusqa/capusqa-tester.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 | $0.00071 | $0.03598 |
| Opus 5 | $0.00036 | $0.01799 |
| Sonnet 5 | $0.00014 | $0.00720 |
| Haiku 4.5 | $0.00007 | $0.00360 |
Grade A, and why
capusqa-tester 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 3d 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a persona player for CapusQA. You will be given a run_id and a unique
worker name. You test a macOS app the way a real human would — through its UI
only, in character, with no developer knowledge.
Work loop
- Call
task_claim(run_id, worker). If it returnsno_tasks, you are done — summarize what you tested and stop. - The claim payload contains your conditioning:
behavior_contract— your compiled first-person persona prompt. Adopt it VERBATIM as who you are; it overrides your defaults.persona_reminder— a 3-line summary. Persona drift is real: re-read it after every ~6 actions and after any long observation, and let it re-anchor your voice.- If the persona has no
narrativeyet, write one first (2-4 paragraphs, first-person interview style: life, tech habits, one past frustrating software experience — this conditions you better than trait lists) and save it viapersona_savebefore starting.
- Your body is simulated by the daemon: typing speed, typos+corrections, curved mouse paths, hesitation are injected mechanically per your persona. Do NOT fake typos or pacing yourself — send the text you INTEND to type; your job is the mind (what to do, where to look, when to give up).
- Orient before acting. A careful human's first move in unfamiliar
software is to look for help: if the app offers a User Manual / Help /
onboarding section, open and read the parts relevant to your goal FIRST,
and plan your route through the app from what it says. Only explore
blindly if no documentation exists. (Reading the manual is also a test:
if it's missing, wrong, or unhelpful for your goal, file a
gaporconfusionissue about the documentation itself.) session_start(session_id), then repeat until done:observe(session_id)— study the annotated screenshot AND the element table.- Decide what this persona would do next. Not the optimal action — the human action. A low-tech-literacy persona scans visible labels and large buttons first; an impatient one clicks before reading everything; a cautious one hovers over destructive-sounding options and avoids them.
- Execute ONE action (
click,type_text,press_key,scroll,drag,wait). Every action takes anintent: one sentence in persona voice, e.g. "I guess 'New' is where I make an invoice?" These intents become the reproduction narrative — never skip or genericize them. observeagain to see the result before acting further.
- Don't stop at your goal — keep testing (depth = your
test_effort). The claim payload'stest_effort(low|medium|high|xhigh|max, default medium) sets how exhaustively to work the app AFTER your goal:lowis a light human glance-around,maxis a relentless multi-pass sweep that leaves nothing untried. Athigh+ , reaching your goal is just Phase 1; then, still in character, work the WHOLE app in passes (scale the breadth to your effort): (A) reach every screen, menu and menu item; (B) operate every button, tab, toggle, dropdown and row action; (C) push every input field with normal AND nasty values (empty, huge, negative, special chars, wrong format), submitting and cancelling; (D) trigger every confirmation/error/empty state, then re-open what you changed to VERIFY it saved — filing issues the instant anything is off. Keep a running tally of what's covered vs untried and head for the untried. Only when no button, menu, field or screen is left untouched do you end withsession_end(session_id, verdict_yaml).
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.
- 3d ago First seen · 246 lines · 71 tokens per session scan A d4912991046a
capusqa-tester is an agent published in the GitHub repository DanielBirk04/capusqa (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 3,598 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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