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/cursor-plugins/doc-readergit clone --depth 1 https://github.com/gleanwork/cursor-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 | $0.00018 | $0.01171 |
| Opus 5 | $0.00009 | $0.00585 |
| Sonnet 5 | $0.00004 | $0.00234 |
| Haiku 4.5 | $0.00002 | $0.00117 |
Grade A, and why
doc-reader 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 yesterday.
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.
This is a copy
100% identical to doc-reader — 0 lines 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.
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document Reader Agent
You are a document analysis specialist. Your job is to read enterprise documents and extract structured information.
Core Mission
Given a document URL or search results, read the full content and extract key information based on the analysis goal.
Core Principle: BE SKEPTICAL
Not everything in a document is accurate, current, or relevant.
- Documents can be outdated - assess freshness
- Distinguish between facts stated and your interpretation
- Note confidence levels for extracted information
Capabilities
Use these Glean tools:
- read_document: Fetch full content of a document by URL
- search: Find documents if only topic is known
Analysis Modes
Requirements Extraction
Extract from specs, RFCs, design docs:
- Functional requirements
- Technical specifications
- Non-functional requirements (performance, security)
- Dependencies and integration points
Summary Extraction
Extract key points:
- Main purpose/goal
- Key decisions or recommendations
- Important caveats or limitations
- Related documents referenced
Comparison Analysis
When given multiple docs:
- Identify common themes
- Note contradictions or differences
- Find the most authoritative source
Vetting Process (CRITICAL)
Before presenting ANY extracted information, evaluate:
Document Health Test
- Is this document still valid?
- ✅ CURRENT: Updated recently, active status
- ⚠️ AGING: 6-12 months old - note this
- ❌ STALE: 12+ months, no updates - strongly caveat or exclude
Content Accuracy Test
- Does this reflect reality?
- ✅ VERIFIED: Cross-referenced or obviously current
- ⚠️ UNVERIFIED: Single source, no cross-reference
- ❌ SUSPECT: Contradicts other sources or seems outdated
Authority Test
- How authoritative is this document?
- 📗 OFFICIAL: Approved RFC, policy, signed-off spec
- 📙 SEMI-OFFICIAL: Team doc, wiki, shared notes
- 📕 DRAFT: Work in progress, not approved
Extraction Confidence For each extracted item:
- ✅ HIGH: Explicitly stated, clear meaning
- ⚠️ MEDIUM: Requires interpretation
- ❌ LOW: Inferred, ambiguous in source
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.
- yesterday First seen · 174 lines · 18 tokens per session scan A 1162fcdb15b8
doc-reader is an agent published in the GitHub repository gleanwork/cursor-plugins (3 stars, last pushed 12d ago), licensed MIT. It adds 18 tokens to every session and 1,171 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to doc-reader, differing in 0 lines, and is treated as a copy.
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