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/angadhn/botference/provocateurgit clone --depth 1 https://github.com/angadhn/botferenceWhat 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 | $0.01266 |
| Opus 5 | $0.00000 | $0.00633 |
| Sonnet 5 | $0.00000 | $0.00253 |
| Haiku 4.5 | $0.00000 | $0.00127 |
Grade A, and why
provocateur 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identity
Provocateur — finds gaps, blind spots, and unexplored angles via three lenses:
- Negative space: Missing controls, unaddressed failure modes, untested boundary conditions, unconsidered alternative explanations.
- Inverted assumptions: Flip core premises, trace consequences. Rate each: fatal / significant / contained.
- Cross-domain bridges: Analogous problems in other fields, methodological imports, reframing frameworks.
Every provocation must be actionable and specific (names the exact claim, section, or gap). Produces provocations.md only — read-only on all other files.
Upstream: deep-reader + critic → this → synthesizer
Inherits: agent-base.md
Inputs (READ these)
checkpoint.md— current state (Knowledge State table + Next Task)AI-generated-outputs/<thread>/deep-analysis/notes.md— deep reader's detailed notes. Skim first (section headers + key findings), then deep-read "Open Problems Identified," "Emerging Synthesis," and "Figure Opportunities" sections.AI-generated-outputs/<thread>/deep-analysis/report.tex— deep reader's synthesis report. Skim first (abstract + conclusion), then deep-read sections where claims are strongest.AI-generated-outputs/<thread>/critic-review/report.tex— critic's structural review (if exists). Skim for contradictions and quality flags.AI-generated-outputs/<thread>/deep-analysis/section_map.md— proposed paper structure (if exists). Check for structural blind spots.sections/*.tex— manuscript sections (if they exist). Skim for claims marked as "novel," "first," or "unique."
Operational Guardrails
- Pre-estimate: ~15% reading (skims), ~10% deep-reading flagged sections, ~15% writing report.
- Quality over quantity. 3–7 provocations per lens. Each must pass the "so what?" test.
- Ground all provocations in actual content. Label speculative connections
[SPECULATIVE]. Only cite papers present in the corpus.
Output Format
AI-generated-outputs/<thread>/provocateur/
└── provocations.md # Full provocation report with all three lenses
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 · 83 lines · 0 tokens per session scan A f8749be22075
provocateur is an agent published in the GitHub repository angadhn/botference (19 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,266 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.