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 commands/witt3rd/claude-plugins/_shared_content_synthesisgit clone --depth 1 https://github.com/witt3rd/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 | $0.00000 | $0.01748 |
| Opus 5 | $0.00000 | $0.00874 |
| Sonnet 5 | $0.00000 | $0.00350 |
| Haiku 4.5 | $0.00000 | $0.00175 |
Grade A, and why
_shared_content_synthesis 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.
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.
Shared Content Synthesis Instructions
This file contains common instructions for all content ingestion commands (/youtube-transcript, /scrape-url, /process-pdf). These steps apply AFTER content has been acquired, regardless of source.
Universal Content Processing Pipeline
Phase 1: Question-Oriented Content Synthesis
Apply the methodology from thinking_question_content_synthesis.md:
Step 1: Central Question Discovery
- Identify the single overarching question the content addresses
- Consider title, description, opening/closing statements
- This becomes the note's organizing principle
Step 2: Domain Question Extraction
- Identify major question domains by analyzing topic transitions
- Look for transitional phrases: "Now let's talk about," "Another important point," "Moving on to"
- Group content segments into substantial domain areas
Step 3: Specific and Atomic Question Decomposition
- Break domain questions into specific questions (section level)
- Further decompose into atomic questions (evidence level)
- Extract specific details, examples, data points, and quotes from content
Step 4: Progressive Answer Development
- Build comprehensive answers using evidence from content
- Synthesize atomic answers into specific section responses
- Integrate specific answers to address domain questions
- Combine domain insights to resolve central question
Phase 2: Note Structure and Metadata
Generate note filename (if not provided):
- Based on central question or primary topic
- Use lowercase with underscores
- Follow naming convention:
topic_subtopic.mdormoc_topic.md - Examples:
agents_reasoning_patterns.md,python_async_programming.md
Determine appropriate tags:
- 3-6 tags mixing dimensions:
- Technology/Language (
#python,#rust,#typescript) - Framework/Tool (
#mcp,#react) - Domain/Discipline (
#agents,#llm,#writing) - Content Type (
#guide,#reference,#pattern) - Method/Thinking (
#first-principles,#systems-thinking)
- Technology/Language (
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 · 222 lines · 0 tokens per session scan A 5f049b38c987
_shared_content_synthesis is a command published in the GitHub repository witt3rd/claude-plugins (2 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,748 tokens. 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 2026-08-31.
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
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converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.