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/star-ga/mind-memnpx agentmods add skills/star-ga/mind-mem/apply-proposalWrote 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/star-ga/mind-mem/apply-proposal)<a href="https://agentmods.dev/skills/star-ga/mind-mem/apply-proposal"><img src="https://agentmods.dev/badge/skills/star-ga/mind-mem/apply-proposal/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/star-ga/mind-mem/apply-proposal"><img src="https://agentmods.dev/badge/skills/star-ga/mind-mem/apply-proposal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00352 |
| Opus 5.5 | $0.00000 | $0.00141 |
| Sonnet 5.5 | $0.00000 | $0.00070 |
| Haiku 4.5 | $0.00000 | $0.00035 |
Grade A, and why
apply-proposal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- apply-proposal — 100% identical, 0 lines differ
What it actually says
/apply — Apply Proposals
Review and apply intelligence proposals generated by /scan. Uses atomic operations with rollback safety.
When to Use
- After /scan generates proposals in
intelligence/proposed/ - During weekly triage sessions
- When proposals have been manually reviewed and approved
How to Run
Dry Run (recommended first)
python3 maintenance/apply_engine.py P-20260213-001 "${MIND_MEM_WORKSPACE:-.}" --dry-run
Apply a Proposal
python3 maintenance/apply_engine.py P-20260213-001 "${MIND_MEM_WORKSPACE:-.}"
Rollback to Snapshot
python3 maintenance/apply_engine.py --rollback 20260213-143052 "${MIND_MEM_WORKSPACE:-.}"
Safety Protocol
- Always dry-run first — See what would change before applying
- Engine takes a state snapshot before any mutations
- If any post-check fails, all changes roll back automatically
- Applied proposals produce a receipt in
intelligence/applied/<timestamp>/APPLY_RECEIPT.md - Rejected proposals are marked with reason
Proposal Types
DECISIONS_PROPOSED.md— New decisions to formalizeTASKS_PROPOSED.md— New tasks to createEDITS_PROPOSED.md— Edits to existing blocks (supersede, status change)
Triage Actions
- ACCEPT — Apply the proposal
- DEFER — Revisit later (stays in proposed)
- REJECT — Dismiss with reason
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.
- 2mo ago First seen · 43 lines · 0 tokens per session scan A 70303ec07ba5
apply-proposal is a skill published in the GitHub repository star-ga/mind-mem (19 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 352 tokens. 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 2026-08-30.
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