Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Borda/AI-Rignpx agentmods add skills/borda/ai-rig/code-remediateWrote 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/borda/ai-rig/code-remediate)<a href="https://agentmods.dev/skills/borda/ai-rig/code-remediate"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/code-remediate/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/borda/ai-rig/code-remediate"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/code-remediate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Tool Misuse · line 129 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
- medium Excessive Agency · line 310 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00034 | $0.35681 |
| Opus 5.5 | $0.00014 | $0.14272 |
| Sonnet 5.5 | $0.00007 | $0.07136 |
| Haiku 4.5 | $0.00003 | $0.03568 |
Grade A, and why
code-remediate 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Never inspect/edit PR code from `curl`, `raw.githubusercontent.com`, or copied `head-files/` snapshots; raw-file snapshot rejection: snapshots are rejected. How it starts
The opening of the file, as written. The whole thing — 877 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before asking, read User Questions.
Code Remediate
Apply the shared Proportional Execution policy to bounded analysis or implementation delegated within this workflow; specialized source selection, protected-state, lifecycle, and verification gates remain authoritative.
Code Remediate is a single pass: collect findings, resolve the selected work, verify, and report. This specialized contract takes precedence over generic plan-challenge and review-to-fix convergence rules. No convergence score, loop ledger, or score-based stop applies to ordinary remediation. Single pass limits workflow expansion, not necessary debugging, regression repair, or rerunning a failed configured check within the authorized scope.
Challenge Resolve is opt-in: a Code Remediate invocation alone does not authorize the challenge-resolve skill or any iterative adversarial review-and-fix loop, including plan challenges and checkout recovery. Enter that separate workflow only when the user explicitly requests it. Do not propose or ask approval for an unsolicited loop. Existing explicit approval for the same scope remains valid; do not ask again. Only an explicitly requested loop reads ../../shared/adversarial-loop.md and applies its convergence and stop rules; afterward resume remediation's selection, implementation evidence, and normal completion gates. An unavailable recovery route remains explicitly blocked rather than bypassed.
See the fixed recurrence and root-cause policy and reasoning-progress escalation policy for repeated-obstacle handling; record and validate reasoning-progress.json before another cycle after escalation trigger.
Newly discovered in-scope defects do not trigger another review wave or score-based permission request. Resolve feasible work within the authorized scope using source evidence and focused checks; record genuinely separate or unfinished work with evidence, owner, and next action. Ask only for a concrete missing decision or material scope expansion. Never claim unresolved selected findings are closed.
Apply Worktree lifecycle before collection: capture the original invoking checkout and announce any temporary worktree and intended return destination. Review isolation does not make remediation worktree-only; absent an explicit worktree-only request, finished changes belong in the invoking checkout.
Keep report and reviewer setup subordinate to selected finding closure under the primary-goal rules in Reasoning-Progress Escalation. After selection and root-cause evidence establish an authorized fix, implement it and its regression before another review-preparation cycle. Diagnose an agent-owned setup failure once and attempt one bounded repair; if it fails, stop that auxiliary route and continue safe primary work. Preserve missing review coverage as a factual limitation; do not ask the user to debug reviewer names, commands, or metadata.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · -73 lines · +6 tokens per session 2aa43389aa95
- 8d ago Changed · +18 lines 4ae8e8d3683a
- 9d ago Changed · +26 lines fb7abb6f3e1f
- 10d ago Changed · +21 lines ee42f801a514
- 11d ago Changed · +35 lines 107430113595
- 15d ago Changed · +14 lines 419a221e193a
- 16d ago Changed d64a1376ce4d
- 17d ago Changed · +28 lines b08f12271368
- 18d ago Changed · +2 lines 34a47361215f
- 19d ago First seen · 806 lines · 28 tokens per session scan A e6e5f761aa55
code-remediate is a skill published in the GitHub repository Borda/AI-Rig (28 stars, last pushed today), licensed Apache-2.0. It adds 34 tokens to every session and 35,681 once invoked, about $0.0001 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 2026-09-03.
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