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 wpsnote/wpsnote-skills --skill ie-recall-memorygit clone --depth 1 https://github.com/wpsnote/wpsnote-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/wpsnote/wpsnote-skills/ie-recall-memory)<a href="https://agentmods.dev/skills/wpsnote/wpsnote-skills/ie-recall-memory"><img src="https://agentmods.dev/badge/skills/wpsnote/wpsnote-skills/ie-recall-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/wpsnote/wpsnote-skills/ie-recall-memory"><img src="https://agentmods.dev/badge/skills/wpsnote/wpsnote-skills/ie-recall-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 | $0.00073 | $0.00518 |
| Opus 5.5 | $0.00029 | $0.00207 |
| Sonnet 5.5 | $0.00015 | $0.00104 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
insight-recaller 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 1mo 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
WPS Insight Recaller 2.0
Follow the shared workflow in ../wps-learning-workflow.md.
Inputs
- 当前正在处理的一篇 WPS 笔记、写作任务或复习主题
- 可能相关的旧 WPS 笔记
- 可选的时间范围或任务上下文
Output
A structured WPS-ready 选择性召回结果，指出当前最值得重看的旧笔记和可直接复用的内容。
What this skill should produce
重点不是“多找一些相似笔记”，而是召回当下最有价值的旧内容。
建议包含这些部分：
most useful prior notes nowwhy each is worth recallinghow it connects to the current taskwhat can be reused directlywhere to insert or link it
This skill should recall useful prior notes, not perform full cross-note mapping.
WPS-first rules
- 输出时要写明旧笔记标题，方便用户直接在 WPS 里找到。
- 如果拿不到原段落，就做可信的概括，不要伪装成精确引用。
- 召回数量宁少勿滥，优先高价值内容。
Quality rules
- 优先挑“现在就用得上”的旧笔记，而不是“有点像”的旧笔记。
- 尽量在理论、对比、案例之间做平衡，不要只召回同一种内容。
- 对“可直接复用”和“适合后面展开”的内容要区分清楚。
Do not use when
- 目标是建立明确的笔记双链或关系图
- 用户真正想做的是大范围综述，而不是选择性召回
- 没有足够有意义的旧笔记可供召回
Recommended next skill
Usually recommend:
study-note-linkerclass-note-builder
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.
- 1mo ago First seen · 59 lines · 73 tokens per session scan A 2b5bc68e51e7
insight-recaller is a skill published in the GitHub repository wpsnote/wpsnote-skills (183 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 518 once invoked, about $0.0003 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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remem
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evo-memory-review
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ai-memory-coding-conventions
Project coding conventions extracted from chat history. Load when writing new code, naming things, designing APIs, or reviewing PRs. Topics: Cursor pagination is mandatory for all paged GraphQL endpoints.
ai-memory-decision-log
Technical decisions made for this project, with reasoning and rejected alternatives. Load when proposing architectural changes, evaluating alternatives, or asked why a choice was made. Topics: Adopt OAuth 2.0 authorization code flow with PKCE for the customer portal SPA.
ai-memory-system-architecture
System architecture facts: components, data flow, integration boundaries. Load when implementing cross-component features, debugging integration issues, or onboarding to the codebase. Topics: Event sourcing for the billing audit log.