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 finding-to-verified-remediationgit 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/finding-to-verified-remediation)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/finding-to-verified-remediation"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/finding-to-verified-remediation/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/finding-to-verified-remediation"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/finding-to-verified-remediation.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 | $0.00026 | $0.00692 |
| Opus 5.5 | $0.00010 | $0.00277 |
| Sonnet 5.5 | $0.00005 | $0.00138 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
finding-to-verified-remediation 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finding to Verified Remediation
Outcome
Produce a validated security finding and an owned remediation ledger. A proposed fix, merged change, deployed build, passing retest, accepted risk, and closed finding are different states.
When to use
Use for one finding within written asset and method scope when assessment and remediation need accountable owners. A read-only export can support first triage. An Access Review Analyst may supply separately validated permission evidence, but is not an automatic slot in this route.
Discovery and user direction
Inspect existing Security Crews, scope authorization, current finding and asset state, severity policy, issue, change, deployment, retest sources, and closure authority. Propose reuse or reviewed creation. Show the exact route before Builder applies it; selection leaves setup pending.
Required inputs
Bind tenant, finding ID, asset, affected environment and build, scope authorization, allowed methods, source report, severity rule, owner, fix criterion, independent retest rule, and closure policy.
Plan and AgentWorks tools
Reuse Security Findings Analyst and Security Remediation Coordinator. Findings writes security-finding/v1 with applicability and source evidence. Run the bundled validator before Remediation consumes it. Remediation re-reads current source state and writes security-remediation-ledger/v1 with issue, reviewed change, deployment, retest, and disposition. Add explicit validator steps in the Workflow. Require separate authorization for any ticket, code, deployment, scan, or closure write.
Knowledge and persistence
Save scope, tenant, finding, asset, environment, observed and deployed build, policy, issue, change, approval, deployment, retest, disposition, run, and action IDs. Re-read current finding and deployment before repeats; retain failed retests and earlier risk decisions.
Validation and reporting
The validator checks exact joins, scope, applicability, evidence, deployment, retest identity, and closure gates. Fictional finding and remediation ledger pass in their open state; the merged-only closure fails. A separate verified ledger shows the evidence required for closure. The reporting dashboard distinguishes unconfirmed, owned, change pending, deployed, retest blocked, verified, accepted risk, and closed states with restricted source references and cost.
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/invalid-security-remediation-ledger.json 614 B
- examples/security-finding.json 625 B
- examples/security-remediation-ledger.json 708 B
- examples/verified-security-remediation-ledger.json 1.2 KB
- playbook.json 4.6 KB
- references/team-and-handoffs.md 3.3 KB
- scripts/test_validate_handoff.py 3.1 KB runs code
- scripts/validate_handoff.py 7.3 KB runs code
- SETUP.json 3.0 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 · 48 lines · 26 tokens per session scan A 7dfe1daa3a03
finding-to-verified-remediation is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 26 tokens to every session and 692 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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