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 skills/sunil-goyal-1502/project-memory/memory-compactnpx skills add sunil-goyal-1502/project-memory --skill memory-compactgit clone --depth 1 https://github.com/sunil-goyal-1502/project-memoryWrote 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/sunil-goyal-1502/project-memory/memory-compact)<a href="https://agentmods.dev/skills/sunil-goyal-1502/project-memory/memory-compact"><img src="https://agentmods.dev/badge/skills/sunil-goyal-1502/project-memory/memory-compact.svg" alt="Measured on agentmods" 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 | $0.00006 | $0.00446 |
| Opus 5 | $0.00003 | $0.00223 |
| Sonnet 5 | $0.00001 | $0.00089 |
| Haiku 4.5 | $0.00001 | $0.00045 |
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 4d 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
Compact Project Decisions
Reduce the size of the decision store by merging related decisions, removing superseded ones, and deduplicating.
Steps
-
Read
.ai-memory/decisions.jsonland parse all decisions.- If fewer than 5 decisions, tell the user compaction isn't needed yet.
-
Read
.ai-memory/metadata.jsonand check the token count.- Report current count to user.
-
Analyze decisions for compaction opportunities:
Look for these patterns:
- Duplicates: Decisions with essentially the same meaning (even if worded differently)
- Superseded: A later decision that overrides an earlier one (e.g., "Using MySQL" then later "Switched to PostgreSQL" — keep only the latter)
- Mergeable: Multiple decisions in the same category that can be combined into one (e.g., three naming conventions → one combined convention)
-
Produce a compacted set of decisions:
- For merged entries, use the oldest timestamp from the merged decisions
- Preserve all categories
- Keep
confidenceas the max of merged entries - Set
sourceto "compacted" - Add a note in rationale about what was merged if helpful
- Preserve any "unresolved" decisions unless they were clearly resolved by later decisions
-
Show the proposed changes to the user:
- Decisions to remove (with reason: duplicate/superseded)
- Decisions to merge (showing before → after)
- Ask user to confirm before applying
-
Write the compacted decisions back to
.ai-memory/decisions.jsonl(overwrite the file). -
Run sync to update tool-specific files:
node -e "require('${CLAUDE_PLUGIN_ROOT}/scripts/sync-tools.js').syncAll(process.cwd())" -
Report results: Show before/after decision count and estimated token savings.
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.
- 4d ago First seen · 46 lines · 6 tokens per session scan A ceb7e050ff6a
memory-compact is a skill published in the GitHub repository sunil-goyal-1502/project-memory (8 stars, last pushed 4mo ago), licensed MIT. It adds 6 tokens to every session and 446 once invoked, about $0.0000 per session on Opus 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 2026-08-31.
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