internal_search

internal_search is a skill for Claude Code, Codex from shikidmsh-rgb/mochibot. It costs 18 tokens per session (378 once invoked), scanned A, original, MIT.

A local search tool for finding words or phrases in saved conversations, diary entries, and memory. It does not make external requests or change the stored material.

In plain words
What is it for?
Use it to look up earlier decisions, notes, or conversation details by keyword or phrase.
Why use it?
It avoids manually reviewing old chat records and helps recover relevant past information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to look up earlier decisions, notes, or conversation details by keyword or phrase.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shikidmsh-rgb/mochibot/internal_search
Install

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.

Any agent
npx skills add shikidmsh-rgb/mochibot --skill internal_search
Clone the repo
git clone --depth 1 https://github.com/shikidmsh-rgb/mochibot

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for internal_search

README.md
[![agentmods](https://agentmods.dev/badge/skills/shikidmsh-rgb/mochibot/internal_search/github.svg)](https://agentmods.dev/skills/shikidmsh-rgb/mochibot/internal_search)
Your own site
<a href="https://agentmods.dev/skills/shikidmsh-rgb/mochibot/internal_search"><img src="https://agentmods.dev/badge/skills/shikidmsh-rgb/mochibot/internal_search/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.

agentmods 80×15 button for internal_search

Your own site · 80×15
<a href="https://agentmods.dev/skills/shikidmsh-rgb/mochibot/internal_search"><img src="https://agentmods.dev/badge/skills/shikidmsh-rgb/mochibot/internal_search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 378 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.00378
Opus 5.5 $0.00007 $0.00151
Sonnet 5.5 $0.00004 $0.00076
Haiku 4.5 $0.00002 $0.00038

Measured 19d ago against content hash 4abcf16aabdf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

internal_search 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 19d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (__init__.py, handler.py, queries.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

mochi/skills/internal_search/SKILL.md · 33 lines

What it actually says

Tools

search_personal_history (on_demand, adaptive)

在本地保存的聊天记录、Diary 和 Memory 中搜索关键词或短语。

Parameter Type Required Description
query string yes 要查找的关键词或短语,最多 200 个字符
source string (enum: all, conversation, diary, memory) no 搜索范围,默认 all
limit integer no 每类最多返回条数,默认 5,范围 1-10

read_tool_result (on_demand, adaptive)

翻看一张回执对应的详细结果,不会重新执行原操作。长内容可以接着读;当时没有完整保留下来的内容会注明。

Parameter Type Required Description
receipt_id integer yes 要查看的回执编号。
offset integer no 从上次返回的 next_offset 继续读;首次可省略。

Capability Context

  • 搜索只读取 MochiBot 本地保存的资料,不会发起外部请求或修改记忆内容。
  • all 会分别返回聊天、Diary 和 Memory 片段。
  • 聊天和 Diary 使用文字匹配,Memory 使用已有的本地文字召回能力;聊天结果不包含当前这一轮的用户消息。
  • 显式搜索覆盖仍保留的历史记录,包括 /reset 之前的记录;/reset 不删除资料。
  • Diary 只搜索“今日日記”正文,不搜索状态区或明天草稿。
Files

What ships with it

3 files 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.

Changes

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.

  1. 19d ago Changed 4abcf16aabdf
  2. 21d ago Changed · +8 lines 52def976a568
  3. 1mo ago Changed 18bc2d1fa008
  4. 1mo ago First seen · 25 lines · 18 tokens per session scan A e1fe82e819b7

Subscribe to this mod's changes

internal_search is a skill published in the GitHub repository shikidmsh-rgb/mochibot (105 stars, last pushed 18d ago), licensed MIT. It adds 18 tokens to every session and 378 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 2026-09-24.

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