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.
git clone --depth 1 https://github.com/nathanimphilipos/synergos-grcWrote 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/commands/nathanimphilipos/synergos-grc/sar-response)<a href="https://agentmods.dev/commands/nathanimphilipos/synergos-grc/sar-response"><img src="https://agentmods.dev/badge/commands/nathanimphilipos/synergos-grc/sar-response/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/commands/nathanimphilipos/synergos-grc/sar-response"><img src="https://agentmods.dev/badge/commands/nathanimphilipos/synergos-grc/sar-response.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 | $0.00006 | $0.01246 |
| Opus 5 | $0.00003 | $0.00623 |
| Sonnet 5 | $0.00001 | $0.00249 |
| Haiku 4.5 | $0.00001 | $0.00125 |
Grade A, and why
sar-response 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 10d 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.
This is a copy
100% identical to sar-response — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/grc:sar-response
Help draft structured responses to SAR (Security Assessment Report) findings.
Usage
/grc:sar-response [framework?] [action?]
The user pastes a SAR finding after invoking the command.
Arguments
- framework (optional):
fedramp,nist,fisma. Defaults tofedramp. - action (optional):
respond(default): Draft a structured response to a findingdisagree: Draft a response disagreeing with a finding (false positive or risk acceptance)template: Show the blank response template structure
Examples
/grc:sar-response fedramp
/grc:sar-response fedramp respond
/grc:sar-response fedramp disagree
/grc:sar-response template
Behavior
When invoked:
-
Display the Data Sensitivity Notice at the top of every response (see SKILL.md Data Handling section). SAR findings may contain system-specific vulnerability details.
-
Read the appropriate reference files:
skills/grc-knowledge/audits/sar-response-patterns.mdfor response templates and quality checklistskills/grc-knowledge/audits/document-section-requirements.mdfor POA&M field requirementsskills/grc-knowledge/conmon/poam-management.mdfor severity SLAs
-
For
respondaction:Analyze the pasted finding and generate a structured response covering:
a. Acknowledgment
- Confirm understanding of the finding
- Note agreement or partial agreement
b. Root Cause Analysis
- Suggest root cause categories based on the finding type (operational, documentation, technical)
- Provide placeholder language the user can customize
- Avoid suggesting root causes that evaluate security posture
c. Remediation Plan
- Suggest specific, actionable remediation steps
- Include role placeholders for responsible parties
- Calculate target dates based on severity SLA
- Suggest granular milestones (not just "remediate")
d. Interim Mitigations
- Suggest interim mitigations appropriate to the finding type
- For Critical/High: emphasize urgency of interim controls
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.
- 10d ago First seen · 159 lines · 6 tokens per session scan A d9f9ffd5be22
sar-response is a command published in the GitHub repository nathanimphilipos/synergos-grc (5 stars, last pushed 6mo ago), licensed MIT. It adds 6 tokens to every session and 1,246 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sar-response, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.