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 agentmods add commands/waittim/memorycustodian/memory-compactgit clone --depth 1 https://github.com/waittim/MemoryCustodianWhat 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 | $0.00000 | $0.00295 |
| Opus 5 | $0.00000 | $0.00148 |
| Sonnet 5 | $0.00000 | $0.00059 |
| Haiku 4.5 | $0.00000 | $0.00030 |
Grade A, and why
memory-compact 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 3d 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.
What it actually says
memory-compact
Run a dry run first:
memory-custodian compact
The report lists exact duplicate top-level bullet units, exact tombstone matches, and candidates requiring Agent review. Each top-level bullet unit includes its continuation and nested lines; nested bullets are never cleanup candidates on their own. For each candidate, determine scope, type, confidence, and whether equivalent memory already exists. Then edit the appropriate Markdown directly or use memory-custodian add.
If the exact mechanical cleanup is appropriate, run:
memory-custodian compact --apply --confirm-plan <PLAN_ID>
This command does not classify or promote candidates. It only removes the exact duplicate complete units and tombstone matches shown in the preview; reviewed candidates remain in the inbox until handled explicitly. Run memory-custodian check after semantic updates.
For an over-budget active file, run a target dry run:
memory-custodian compact --target decisions.md
First shorten decisions over 120 tokens, merge superseded entries, move subsystem knowledge into matched areas, and retain active invariants in normal loading paths. Then apply only after reviewing the plan:
memory-custodian compact --target decisions.md --apply --archive-oldest --confirm-plan <PLAN_ID>
For semantic compaction, read skills/memory-custodian/references/compaction-policy.md and update memory files directly.
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.
- 3d ago First seen · 32 lines · 0 tokens per session scan A 475b2ef45ee8
memory-compact is a command published in the GitHub repository waittim/MemoryCustodian (20 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 295 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.
Other commands, from other repositories
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
OpenSpec: Apply
Implement an approved OpenSpec change and keep tasks in sync.
diff
Compare two SKILL.md files section-by-section. Parses frontmatter and body sections independently, showing exactly what changed.
commit
智能生成 Git 提交信息并提交.
pr
Handle the full workflow from current branch state to an open, CI-monitored pull request.
aidd-pr
Review a PR, resolve addressed comments, and generate /aidd-fix delegation prompts for remaining issues.