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/score-maturity)<a href="https://agentmods.dev/commands/nathanimphilipos/synergos-grc/score-maturity"><img src="https://agentmods.dev/badge/commands/nathanimphilipos/synergos-grc/score-maturity/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/score-maturity"><img src="https://agentmods.dev/badge/commands/nathanimphilipos/synergos-grc/score-maturity.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 | $0.00012 | $0.01700 |
| Opus 5 | $0.00006 | $0.00850 |
| Sonnet 5 | $0.00002 | $0.00340 |
| Haiku 4.5 | $0.00001 | $0.00170 |
Grade A, and why
score-maturity 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 9d 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 score-maturity — 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/grc:score-maturity
Score control implementation maturity on a 0–5 scale with actionable guidance to reach the next level.
Usage
/grc:score-maturity [framework] [family-or-control] [baseline?]
The user optionally provides implementation descriptions or narrative text. If no content is provided, the command asks structured questions.
Arguments
- framework: The compliance framework. Accepts:
nist,fedramp,fisma,cmmc,soc2,iso27001,pci,hipaa,cis,cobit - family-or-control: A control family (e.g.,
ac,ia) or specific control ID (e.g.,ac-2,ia-2) - baseline (optional):
low,moderate,high. Defaults tomoderatefor NIST/FedRAMP.
Examples
/grc:score-maturity fedramp ac-2
/grc:score-maturity fedramp ac moderate
/grc:score-maturity nist ia
/grc:score-maturity cmmc 3.5
/grc:score-maturity soc2 CC6
/grc:score-maturity cobit DSS02
Behavior
When invoked:
-
Display the Data Sensitivity Notice at the top of every response if the user provides content. If no content is provided and the command enters interactive/question mode, the notice is not needed.
-
Read the appropriate reference files:
skills/grc-knowledge/audits/narrative-quality-criteria.mdfor the 0–5 maturity scale- Framework file from
skills/grc-knowledge/frameworks/for control details
-
Determine mode based on user input:
Mode A: Content-based scoring (user provides narrative or implementation description)
- Score each control directly using the 0–5 maturity scale
- Apply the same criteria as
/grc:review-narrativebut focus on the score and "next level" guidance - For a family, score each control individually and compute an overall family score
Mode B: Question-based scoring (no content provided)
- Ask structured questions about the implementation for each control or the family
- Questions organized around the Five W's and maturity indicators:
For each control, ask about:
- Documentation: Is there a written narrative? How detailed?
- Implementation: Is the control technically implemented? Fully or partially?
- Automation: Is the control automated, manual, or hybrid?
- Repeatability: Is the process consistent and repeatable? Documented procedures?
- Measurement: Are there metrics? How is effectiveness tracked?
- Review: When was the last review? How often?
- Evidence: What evidence exists? Could you produce it for an auditor today?
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.
- 9d ago First seen · 173 lines · 12 tokens per session scan A 9fc7ec6e69a7
score-maturity is a command published in the GitHub repository nathanimphilipos/synergos-grc (5 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 1,700 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to score-maturity, 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.