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 manishiitg/coding-agent-loop --skill access-exception-to-verified-fixgit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/access-exception-to-verified-fix)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/access-exception-to-verified-fix"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/access-exception-to-verified-fix/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/manishiitg/coding-agent-loop/access-exception-to-verified-fix"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/access-exception-to-verified-fix.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 | $0.00025 | $0.00747 |
| Opus 5.5 | $0.00010 | $0.00299 |
| Sonnet 5.5 | $0.00005 | $0.00149 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
access-exception-to-verified-fix 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 20d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Access Exception to Verified Fix
Outcome
Produce a policy-bound access exception, then track an approved fix and independent same-cell retest. Keep proposal, approval, merge, deployment, retest and closure distinct.
When to use
Use when a SaaS team needs to follow a reproducible role, ownership or cross-tenant mismatch through remediation. Use one Access Review Analyst for a standalone permission matrix. Use Finding to Verified Remediation for a general scanner or application finding without an exact permission cell.
Discovery and user direction
Inspect scope, policy revision, actors, fixtures, build, evidence rules, existing Crews, change sources and closure authority. Reuse compatible Crews or propose creation. Show the route before Builder applies it; installation leaves setup pending.
Required inputs
Bind tenant, policy revision, exact actor role and tenant, resource type, resource tenant and ID, action, expected decision, build, environment, direct server test, owner, and restricted evidence policy. A hidden UI control alone cannot prove server denial.
Plan and AgentWorks tools
Access Review Analyst writes access-review-matrix/v1 with one selected failed cell and its direct server attempt. Run the bundled matrix validator before Security Remediation Coordinator consumes it. Remediation re-reads current policy and issue state, records a reviewed change and deployment, then an independent retest of the same cell. Run the bundled remediation validator before reporting closure. Builder must insert these as blocking scripted steps and bind their exact input file paths; merely describing a validator is insufficient. No credential is copied between Crews.
Knowledge and persistence
Save policy, scope, actor/fixture, cell, attempt, trace, build, issue, change, approval, deployment, retest and closure IDs with source times. Preserve failed attempts and earlier decisions. A policy, actor, resource, or build change requires a fresh matrix or explicitly new case; a later run cannot reuse a passing test from a different cell.
What ships with it
9 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.
- examples/access-remediation-pending.json 931 B
- examples/access-remediation-verified.json 1.6 KB
- examples/access-review-matrix.json 1.2 KB
- examples/invalid-access-remediation.json 1.0 KB
- playbook.json 4.7 KB
- references/team-and-handoffs.md 2.4 KB
- scripts/test_validate_handoff.py 2.9 KB runs code
- scripts/validate_handoff.py 8.6 KB runs code
- SETUP.json 2.5 KB
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.
- 20d ago First seen · 49 lines · 25 tokens per session scan A 15200fcfaaf4
access-exception-to-verified-fix is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 25 tokens to every session and 747 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 2026-09-27.
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