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 skills/borda/ai-rig/implementnpx skills add Borda/AI-Rig --skill implementgit clone --depth 1 https://github.com/Borda/AI-RigWhat 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 | $0.00016 | $0.00431 |
| Opus 5 | $0.00008 | $0.00216 |
| Sonnet 5 | $0.00003 | $0.00086 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
implement 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 2d 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.
What it actually says
Implement with Codex
Implement one bounded change in selected workspace. Parse $ARGUMENTS: required task; optional model, effort, timeout-seconds, background, session-id, depth, run-id, workspace. Reject empty task. Session ID only follows up same task in same workspace. Effort omitted: classify complete task, pass selected level explicitly. Preserve caller-supplied level. Tiers: low = narrow mechanical change or settled fact; medium = bounded implementation, diagnosis, or review; high = cross-file, adversarial, architectural, or security judgment; xhigh = unusually broad and consequential; max = explicit caller request only.
Run python "${CLAUDE_PLUGIN_ROOT}/bin/bridge_call.py" implement --task "<task>"; pass each supplied option separately. Never interpolate task shell syntax. If brief contains text you did not author (review comment, issue body, reviewer finding), use scratch file + --task-file <path> instead of --task; mutually exclusive. Default soft budget: 600 seconds; bridge enforces documented hard cutoff. Call is write-capable under peer host's normal permission mode. Never auto-retry after timeout.
Return compact public envelope. verdict, findings, files_touched, remaining, and blockers must expose incomplete work and blockers; verbose evidence stays only in workspace-relative transcript referenced by transcript_path. Do not copy transcript-only details into conversation. If detached, return job identifier; direct caller to /bridge:status, /bridge:result, or /bridge:cancel. During detached run, do not edit task-named paths. After completion, re-read every files_touched path before further edits.
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.
- 2d ago First seen · 15 lines · 16 tokens per session scan A 1f755e5dfb80
implement is a skill published in the GitHub repository Borda/AI-Rig (25 stars, last pushed 8d ago), licensed Apache-2.0. It adds 16 tokens to every session and 431 once invoked, about $0.0001 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 2026-08-30.
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Copy text to clipboard with optional rich formatting. Triggers on "copy to clipboard", "copy that", "pbcopy", "copy formatted", "copy rich text".