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 diagrid-labs/dapr-skills --skill review-agent-memorygit clone --depth 1 https://github.com/diagrid-labs/dapr-skillsWrote 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/diagrid-labs/dapr-skills/review-agent-memory)<a href="https://agentmods.dev/skills/diagrid-labs/dapr-skills/review-agent-memory"><img src="https://agentmods.dev/badge/skills/diagrid-labs/dapr-skills/review-agent-memory/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/diagrid-labs/dapr-skills/review-agent-memory"><img src="https://agentmods.dev/badge/skills/diagrid-labs/dapr-skills/review-agent-memory.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 | $0.00033 | $0.00811 |
| Opus 5.5 | $0.00013 | $0.00324 |
| Sonnet 5.5 | $0.00007 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
review-agent-memory 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.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Agents — Memory and State
Overview
Scans agent memory and state-store configuration (component YAMLs + in-code wiring) for correctness: exactly one actor state store (actorStateStore: "true") for the workflow engine, memory and state wiring that really persists (native dapr-agents memory is per run and moves to the state store whenever state is set; diagrid wrappers keep history per workflow instance only), helper stores that point at loaded components, exact component names for auto-discovery, stable agent names, and secret management for LLM and Catalyst keys. Read-only: this skill never modifies source files.
Execution Order
You MUST follow these phases in strict order.
- Resolve scope — Read
../dapr-shared/review-scope-prompt.mdand follow it to setscope_root. - Detect target — Read
../dapr-shared/review-detect-target-agent.mdand follow it to producelanguage,flavor,agent_files, andcomponent_files. - Load checklist — Based on
language, read exactly one of: - Scan — Apply every rule from the loaded checklist to agent files and component YAMLs. For Python, apply each rule only to files of the flavor it lists; in a
mixedproject, use each file's own flavor. Cross-reference: a rule about a component is only valid if the component name is referenced in code (or conventionally expected, likeagent-workflow). - Report — Format findings using
../dapr-shared/review-report-format.md. Group by severity, then rule id, then file path. - Show final message — Emit the report from step 5 with a
## Next stepsblock.
Prerequisites
- Read access to the project directory.
- No build, compile, or run step required.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · -10 tokens per session 3d115c4d13bf
- 13d ago Changed 4ef4757d5165
- 14d ago Changed eb53a4012208
- 1mo ago First seen · 53 lines · 43 tokens per session scan A 124a709052aa
review-agent-memory is a skill published in the GitHub repository diagrid-labs/dapr-skills (13 stars, last pushed 9d ago), licensed MIT. It adds 33 tokens to every session and 811 once invoked, about $0.0001 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 2026-08-30.
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