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 HigorAlves/orc --skill qa-targetsgit clone --depth 1 https://github.com/HigorAlves/orcWrote 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/higoralves/orc/qa-targets)<a href="https://agentmods.dev/skills/higoralves/orc/qa-targets"><img src="https://agentmods.dev/badge/skills/higoralves/orc/qa-targets/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/higoralves/orc/qa-targets"><img src="https://agentmods.dev/badge/skills/higoralves/orc/qa-targets.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 | $0.00066 | $0.01434 |
| Opus 5.5 | $0.00026 | $0.00574 |
| Sonnet 5.5 | $0.00013 | $0.00287 |
| Haiku 4.5 | $0.00007 | $0.00143 |
Grade A, and why
qa-targets scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `kind: remote` → `orc-targets probe <name>`; failure is an **environment escalation** (`🛑 Escalation — target unreachable`: name, URL, curl exit) — stop, never fall back to local silently. How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA targets
Browser QA runs against a target: local (the Docker env orc-env-provisioner boots) or a remote URL such as staging or a preview deploy. Targets live in <repo>/.orc/targets.json (gitignored, repo-level — not per branch), managed by orc-targets (plugin bin/, on PATH while orc is enabled).
Announce at start: "I'm using the qa-targets skill to resolve where browser QA runs."
Registry shape
{ "schema": 1, "targets": {
"local": { "kind": "local", "baseUrl": null, "healthPath": "/", "guard": false, "users": {}, "login": null },
"staging": { "kind": "remote", "baseUrl": "https://staging.example.com", "healthPath": "/healthz", "guard": true,
"users": { "admin": { "username": "env:STAGING_ADMIN_USER", "password": "op://Eng/staging-admin/password" } },
"login": { "path": "/login", "usernameField": "Email", "passwordField": "Password", "submit": "Sign in", "successPath": "/dashboard" } } } }
kind—localis provisioned byorc:browser-qaStep 0 (today's path, unchanged);remoteis probed, never provisioned.guard: true— a shared environment. The planner is told to tag mutating scenarios@mutating; on a guarded target those run asskippedwith noteguarded target— never silently dropped, never executed.users.<name>.{username,password}— references, not values: a literal,op://vault/item/field(1Password CLI,op read), orenv:VAR.orc-targets resolve <name>substitutes them at run time and prints JSON forORC_TARGET_JSON; the resolved JSON is never written to disk. Unresolvable ⇒ exit 3 ⇒ an escalation, not a skip.login— the recipetests/auth.setup.tsfollows once per run in the video-offsetupproject; the session is saved asstorageStateand reused by every scenario. Field hints match by label or placeholder text.
Resolution order (every caller, same order)
--target <name>flag → use it silently (orc-state decision set target <name> --provenance flag).--web <url>flag (kept for compatibility) → an ad-hoc remote target:orc-targets resolve local --base-url <url>; recorded astarget=adhoc:<url>.- A settled
targetdecision in the session → reuse silently; re-runs keep it. - Otherwise the Target gate below.
guided/fullautopilot:local(policy decision, printed one-liner) — a remote target is a judgment call and is never auto-picked.
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.
- 12d ago First seen · 60 lines · 66 tokens per session scan A 15e9a9a66114
qa-targets is a skill published in the GitHub repository HigorAlves/orc (6 stars, last pushed 10d ago), licensed MIT. It adds 66 tokens to every session and 1,434 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-08.
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