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 skills add dyCuong03/unity-agent-team --skill agentmemory-codebase-recallgit clone --depth 1 https://github.com/dyCuong03/unity-agent-teamWrote 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/dycuong03/unity-agent-team/agentmemory-codebase-recall)<a href="https://agentmods.dev/skills/dycuong03/unity-agent-team/agentmemory-codebase-recall"><img src="https://agentmods.dev/badge/skills/dycuong03/unity-agent-team/agentmemory-codebase-recall/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/dycuong03/unity-agent-team/agentmemory-codebase-recall"><img src="https://agentmods.dev/badge/skills/dycuong03/unity-agent-team/agentmemory-codebase-recall.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 | $0.00055 | $0.02088 |
| Opus 5.5 | $0.00022 | $0.00835 |
| Sonnet 5.5 | $0.00011 | $0.00418 |
| Haiku 4.5 | $0.00006 | $0.00209 |
Grade A, and why
agentmemory-codebase-recall 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agentmemory Codebase Recall
This is a skill pack, not an agent. Load it when triage indicates prior sessions exist for the touched system, or when an investigation, bug-fix, or feature task would benefit from prior architectural knowledge.
Core Contract
agentmemory is a recall layer. It is NOT the source of truth.
Current repo files always win. Memory surfaces candidate files, known pitfalls, and architectural decisions from prior sessions. Every memory hit must be verified against the actual file before being acted on.
| Principle | Meaning |
|---|---|
| Recall before exploration | Query memory before opening files or running Grep |
| Verify before using | Read the current file; memory may be stale |
| Files win on conflict | If memory contradicts current source → trust the file |
| Never edit from memory alone | A memory fact is a hypothesis; code read confirms it |
| Never claim from memory alone | Do not assert architecture facts without file evidence |
Mandatory Flow
agentmemory query
│
▼ candidate files / symbols / known pitfalls
targeted file discovery (Read, Grep on known paths only)
│
▼ current source text
verify memory against files
│
▼ confirmed facts only
analyze / edit / implement
│
▼ after task completes
save findings (mcp__agentmemory__memory_lesson_save or memory_save)
Do NOT skip to "targeted file discovery" without first running the memory query. Do NOT skip the "verify against files" step even if memory looks confident.
Tool Reference
The following tools are confirmed present in this project's MCP configuration. Do NOT invent tool names — use only these.
Note: The canonical source for the agentmemory MCP server capabilities is https://github.com/rohitg00/agentmemory — verify tool names against current docs if the list below ever diverges from actual MCP responses.
Query tools (use BEFORE opening files)
| Tool | When to use |
|---|---|
mcp__agentmemory__memory_smart_search |
First call — natural-language search across all sessions. Pass the symptom, system name, or component name. |
mcp__agentmemory__memory_recall |
Direct recall by tag or session ID when you know the exact context. |
mcp__agentmemory__memory_sessions |
List prior sessions to find relevant context when smart_search returns nothing useful. |
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.
- 11d ago First seen · 224 lines · 55 tokens per session scan A 8c97d181bd52
agentmemory-codebase-recall is a skill published in the GitHub repository dyCuong03/unity-agent-team (7 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 2,088 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-02.
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