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 iusztinpaul/squid --skill squid-implement-taskgit clone --depth 1 https://github.com/iusztinpaul/squidWrote 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/iusztinpaul/squid/squid-implement-task)<a href="https://agentmods.dev/skills/iusztinpaul/squid/squid-implement-task"><img src="https://agentmods.dev/badge/skills/iusztinpaul/squid/squid-implement-task/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/iusztinpaul/squid/squid-implement-task"><img src="https://agentmods.dev/badge/skills/iusztinpaul/squid/squid-implement-task.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00075 | $0.01398 |
| Opus 5.5 | $0.00030 | $0.00559 |
| Sonnet 5.5 | $0.00015 | $0.00280 |
| Haiku 4.5 | $0.00007 | $0.00140 |
Grade A, and why
squid-implement-task 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 today.
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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement Task — inner SWE↔Tester loop (1 or N tasks)
Take a task (or a list of tasks / an approved Tasks Plan) and drive each one through the inner SWE → Tester loop, committing each task once it passes. Runs in whatever working tree it's invoked in — the feature worktree when /squid-implement-night invokes it (pass Working directory: {path} to every agent), your current branch when standalone. No worktrees are created here (that's /squid-plan's job) and no human gates run here (those live in /squid-plan and at the end of /squid-implement-night).
$ARGUMENTS is one of: a single task ref (NNN-slug / #N), a free-form task description, the feature's pending task files (tasks/<NNN>-*.md, status: pending), or several refs. If empty, ask the human what to implement.
You are the orchestrator — a MANAGER, not an implementer. You launch agents, enforce the Tester gate, and commit on green. You do NOT write code, run tests, or review the diff yourself beyond inspection (git diff, git log).
Read AGENTS.md first to confirm the active tracker mode (file or gh) and the project's stack + test commands.
Critical rules:
- Never rubber-stamp the Tester. Spot-check that each AC marked PASS has real evidence (test name, file:line, command output) and that the e2e adversarial section actually attempted break paths. Re-launch with concrete feedback if not.
- One agent per task. Never bundle multiple tasks into one agent call.
- Commit each task on PASS — do NOT push. Pushing, PR creation, acceptance, and review are
/squid-review's job.
Step 1 — Resolve the task list
Build an ordered list of tasks from $ARGUMENTS:
- Tracker ref(s) (
NNN-slug/#N) → load each task'stasks/<NNN>-<slug>.md. - Approved Tasks Plan → the feature's
tasks/<NNN>-*.mdfiles withstatus: pending, inNNNorder (gh mode: the feature's open issues). - Free-form description → a single ephemeral task; don't create a task file unless the human asks.
- Empty → ask the human what to implement.
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.
- today Changed 33ad4c6b4b52
- 1mo ago Changed · -13 lines · -11 tokens per session 6917427dd738
- 1mo ago First seen · 122 lines · 86 tokens per session scan A efc996644a9d
squid-implement-task is a skill published in the GitHub repository iusztinpaul/squid (210 stars, last pushed today), licensed Apache-2.0. It adds 75 tokens to every session and 1,398 once invoked, about $0.0003 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 2026-08-30.
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