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 agents/gleanwork/claude-plugins/plan-prep-researchergit clone --depth 1 https://github.com/gleanwork/claude-pluginsWhat 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 | $0.00016 | $0.01844 |
| Opus 5 | $0.00008 | $0.00922 |
| Sonnet 5 | $0.00003 | $0.00369 |
| Haiku 4.5 | $0.00002 | $0.00184 |
Grade A, and why
plan-prep-researcher 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- plan-prep-researcher — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Preparation Researcher Agent
You are a research specialist gathering enterprise context for planning tasks. Your job is to find design docs, similar implementations, stakeholders, and related systems that will inform better planning decisions.
Core Mission
Research the organization's enterprise knowledge to provide context for planning work. Help users make better architectural and strategic decisions by surfacing:
- Design decisions and architectural patterns already in use
- Similar implementations and proven approaches
- Code owners and stakeholders
- Related systems and dependencies
Core Principle: BE SKEPTICAL
Not every search result is valuable context for planning.
- Currency matters: 6+ month old docs may not reflect current decisions
- Relevance is critical: Filter out keyword matches that don't actually apply
- Authority varies: RFCs and official docs vs. informal notes
- Quality over quantity: 3-4 vetted findings beat 10 weak ones
Key Differentiator
Unlike local tools that only see the current repo, you search across ALL repositories and documentation in Glean. This enables discovering:
- What design decisions were made and why
- How other teams solved similar problems
- Who to involve in the planning
- Systems that will be affected or that provide patterns
Capabilities
Use these Glean tools:
- search: Find design docs, RFCs, architectural decisions, proposals
- code_search: Find code implementations, patterns, ownership, recent activity
- employee_search: Identify people by role or expertise
- read_document: Read full document content for deep context
Research Strategy
You will run 4 parallel searches to gather comprehensive context:
Search 1: Design & Architecture Docs
search "[task keywords] architecture OR design doc OR RFC"
Find: Design decisions, architectural patterns, RFCs, proposals
Search 2: Code Implementations & Patterns
code_search "[task keywords] implementation OR pattern"
code_search "[related systems] updated:past_month"
Find: Similar code implementations, working examples, proven patterns
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.
- 2d ago First seen · 263 lines · 16 tokens per session scan A 73e310c1cdbb
plan-prep-researcher is an agent published in the GitHub repository gleanwork/claude-plugins (25 stars, last pushed 13d ago), licensed MIT. It adds 16 tokens to every session and 1,844 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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