search-strategy

search-strategy is a skill for Claude Code, Codex from kyopark2014/agent-plugins. It costs 43 tokens per session (1,729 once invoked), scanned A, a copy of search-strategy, MIT.

A search-planning skill that breaks a natural-language question into targeted searches across connected sources.

In plain words
What is it for?
It helps investigate decisions, project status, documents, and similar questions across chat, email, knowledge bases, and project trackers, then ranks and synthesizes the findings.
Why use it?
It avoids using one vague search everywhere by choosing source-specific wording, handling ambiguity, and combining duplicate results.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/kyopark2014/agent-plugins/search-strategy
Any agent
npx skills add kyopark2014/agent-plugins --skill search-strategy
Clone the repo
git clone --depth 1 https://github.com/kyopark2014/agent-plugins

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 search-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/kyopark2014/agent-plugins/search-strategy.svg)](https://agentmods.dev/skills/kyopark2014/agent-plugins/search-strategy)
Your own site
<a href="https://agentmods.dev/skills/kyopark2014/agent-plugins/search-strategy"><img src="https://agentmods.dev/badge/skills/kyopark2014/agent-plugins/search-strategy.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,729 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00043 $0.01729
Opus 5 $0.00022 $0.00864
Sonnet 5 $0.00009 $0.00346
Haiku 4.5 $0.00004 $0.00173

Measured 5d ago against content hash 2b06a74db5f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

search-strategy 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 5d 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.

Origin

This is a copy

100% identical to search-strategy — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

application/plugins/enterprise-search/skills/search-strategy/SKILL.md · 222 lines

How it starts

The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Search Strategy

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

The core intelligence behind enterprise search. Transforms a single natural language question into parallel, source-specific searches and produces ranked, deduplicated results.

The Goal

Turn this:

"What did we decide about the API migration timeline?"

Into targeted searches across every connected source:

~~chat:  "API migration timeline decision" (semantic) + "API migration" in:#engineering after:2025-01-01
~~knowledge base: semantic search "API migration timeline decision"
~~project tracker:  text search "API migration" in relevant workspace

Then synthesize the results into a single coherent answer.

Query Decomposition

Step 1: Identify Query Type

Classify the user's question to determine search strategy:

Query Type Example Strategy
Decision "What did we decide about X?" Prioritize conversations (~~chat, email), look for conclusion signals
Status "What's the status of Project Y?" Prioritize recent activity, task trackers, status updates
Document "Where's the spec for Z?" Prioritize Drive, wiki, shared docs
Person "Who's working on X?" Search task assignments, message authors, doc collaborators
Factual "What's our policy on X?" Prioritize wiki, official docs, then confirmatory conversations
Temporal "When did X happen?" Search with broad date range, look for timestamps
Exploratory "What do we know about X?" Broad search across all sources, synthesize

Step 2: Extract Search Components

From the query, extract:

  • Keywords: Core terms that must appear in results
  • Entities: People, projects, teams, tools (use memory system if available)
  • Intent signals: Decision words, status words, temporal markers
  • Constraints: Time ranges, source hints, author filters
  • Negations: Things to exclude

Read the full file on GitHub · 222 lines

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. 5d ago First seen · 222 lines · 43 tokens per session scan A 2b06a74db5f9

Subscribe to this mod's changes

search-strategy is a skill published in the GitHub repository kyopark2014/agent-plugins (4 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,729 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to search-strategy, differing in 1 line, and is treated as a copy.