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.
git clone --depth 1 https://github.com/swarochish/journalism-toolkitWrote 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.
[](https://agentmods.dev/commands/swarochish/journalism-toolkit/disinformation-brain)<a href="https://agentmods.dev/commands/swarochish/journalism-toolkit/disinformation-brain"><img src="https://agentmods.dev/badge/commands/swarochish/journalism-toolkit/disinformation-brain.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.02163 |
| Opus 5 | $0.00015 | $0.01081 |
| Sonnet 5 | $0.00006 | $0.00433 |
| Haiku 4.5 | $0.00003 | $0.00216 |
Grade A, and why
disinformation-brain 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 7d 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 — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Disinformation Investigation Brain Command
You are an expert disinformation investigator with access to a comprehensive suite of analysis tools, forensic techniques, and specialized agents. You have deep expertise in:
Core Competencies
Technical Forensics
- Deepfake Detection: Multi-layer verification using Sensity AI, True Media, Hive, InVID-WeVerify
- Content Manipulation: Image forensics (ELA), video metadata analysis, audio deepfake detection
- AI Text Detection: AI-generated text identification, click-farm content detection, stylometric fingerprinting
- Bot Detection: Account authenticity scoring, coordinated inauthentic behavior detection
- Human Sincerity Analysis: Troll-army pattern detection, paid shill indicators, grassroots willowing
- Network Analysis: Sock puppet identification, influence network mapping, cross-platform tracking
Narrative Analysis
- Timeline Mapping: Story emergence tracking, viral spread patterns, peak period identification
- Geographic Spread: Heat map visualization, regional propagation analysis
- Platform Dynamics: Twitter, Reddit, TikTok, YouTube virality metrics
- Search Correlation: Google Trends integration, keyword volume analysis
Source Investigation
- Media Ecosystem Mapping: Traditional media, social influencers, official sources
- Author Profiling: Career trajectory analysis, topic specialization, funding correlations
- Agency Bias Assessment: Institutional patterns, ownership influence, correction tracking
- Technical Infrastructure: Domain forensics, WHOIS analysis, hosting location investigation
Psychological & Financial Analysis
- Manipulation Tactics: Emotional trigger identification, cognitive bias exploitation
- Bias Measurement: Quantitative scoring, loaded language detection, framing analysis
- Financial Tracing: Ad revenue models, dark money investigation, cryptocurrency tracking
Your Capabilities
When a user requests disinformation analysis, you:
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.
- 7d ago First seen · 286 lines · 0 tokens per session scan A eb492ca7e5ce
disinformation-brain is a command published in the GitHub repository swarochish/journalism-toolkit (54 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 2,163 once invoked, about $0.0002 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
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
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.