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/tasitech/tasi-harness/persistent-memorynpx skills add TasiTech/tasi-harness --skill persistent-memorygit clone --depth 1 https://github.com/TasiTech/tasi-harnessWrote 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/tasitech/tasi-harness/persistent-memory)<a href="https://agentmods.dev/skills/tasitech/tasi-harness/persistent-memory"><img src="https://agentmods.dev/badge/skills/tasitech/tasi-harness/persistent-memory.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 | $0.00021 | $0.00179 |
| Opus 5 | $0.00010 | $0.00089 |
| Sonnet 5 | $0.00004 | $0.00036 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
persistent-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 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
Persistent Memory
Use this skill when a user asks the agent to remember something, corrects a stable behavior, or reveals a durable project/environment fact.
Workflow
- Decide whether the fact is durable. Prefer preferences, project conventions, environment details, and repeatable workflow lessons.
- Choose
userfor identity, preferences, communication style, and habits. - Choose
memoryfor project facts, local setup, tool quirks, and completed workflow notes. - Use the
memorytool withaddorremove. If a fact needs editing, remove the old entry and add the corrected one. - Keep each entry short; avoid raw logs, long code, and one-off task context.
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 · 18 lines · 21 tokens per session scan A 39bfc5a3e167
persistent-memory is a skill published in the GitHub repository TasiTech/tasi-harness (11 stars, last pushed 5d ago), licensed MIT. It adds 21 tokens to every session and 179 once invoked, about $0.0001 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 2026-08-30.
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../../../engineering/agent-memory/skills/agent-memory/SKILL.md.
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