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/assessWrote 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/assess)<a href="https://agentmods.dev/skills/borda/ai-rig/assess"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/assess/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/assess"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/assess.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 | $0.00019 | $0.02297 |
| Opus 5.5 | $0.00008 | $0.00919 |
| Sonnet 5.5 | $0.00004 | $0.00459 |
| Haiku 4.5 | $0.00002 | $0.00230 |
Grade A, and why
assess 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.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before asking, read User Questions.
Assess
Task-size routing follows Proportional Execution; this skill's specialized lifecycle and acceptance checks remain authoritative.
Run evidence-first analysis: truth, risk, next action before implementation, review, release, sync.
Input Schema
{
"question": "required analysis question",
"scope": "required files, diff, issue text, report path, PR number, or repo area",
"mode": "optional local|github|report|ecosystem; default local",
"done_when": "findings are source-backed, ranked, and have explicit confidence"
}
Workflow
For allowed GitHub reads, run the direct helper under current effective network and filesystem grants or request runtime approval for the complete owning command when required capability is unavailable. No separate workflow consent is needed. Apply GitHub Read Execution; an explicit runtime denial or non-overridable restriction stops the attempt.
When runtime permissions show network access enabled and the helper's required paths writable, omit sandbox_permissions and justification on the direct helper call; give no approval brief. Apply GitHub Read Execution even when the active profile name is omitted. A missing label or failed lookup does not mean disabled access; do not run codex execpolicy list to detect a profile. Preserve explicit destination restrictions and check report, .git, and checkout paths separately where applicable.
Codex provides this selected SKILL.md path. Resolve PLUGIN_ROOT as directory two levels above containing skill directory, then use only helpers under PLUGIN_ROOT/shared/ that are listed in package-manifest.json. Never guess cache version or fall back to source checkout.
What ships with it
1 file 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.
- 2d ago Changed 54ac15735e79
- 11d ago Changed · -2 lines 3d1278220ae2
- 22d ago Changed 1a136f532f91
- 26d ago Changed · +2 lines 7addad79d6b8
- 27d ago Changed 331c76ad45e4
- 28d ago Changed a27027c49f91
- 1mo ago Changed · +4 lines 44723d634f48
- 1mo ago Changed · -3 lines 95b4d63470db
- 1mo ago Changed · +2 lines a58c992241ce
- 1mo ago First seen · 162 lines · 19 tokens per session scan A fdffc7d7de52
assess is a skill published in the GitHub repository Borda/AI-Rig (30 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 2,297 once invoked, about $0.0001 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 2026-09-11.
Other skills, from other repositories
auto-test-code
A structured process for critically reviewing and testing software code. It records review findings, test plans, commands, results, and supporting files in a project workspace.
git-pr-review
A read-only reviewer for GitHub pull requests, which are proposed code changes submitted for review. It produces an evidence-based report about whether a pull request should be merged.
code-reviewer
A code-review workflow that checks completed work against its requirements or plan before merging. It groups findings by severity and gives each issue a fix and a way to verify it.
coding-assistant
Provides coding assistance with best practices and code review.
challenge
Use before a root-cause, done/verified claim, irreversible action, or 2nd-time fix reaches the owner (APEX or plain conversation); also fires at every eLicit/Verify gate. Not for code correctness (use sniper).
code-quality
Use when validating code quality after modifications -- SOLID compliance, DRY duplication, linter errors, architecture violations. Do NOT use for functional verification (run verification FIRST, then code-quality).