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 skills add yogsoth-ai/de-anthropocentric-research-engine --skill destructive-ideationgit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/skills/yogsoth-ai/de-anthropocentric-research-engine/destructive-ideation)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/destructive-ideation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/destructive-ideation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/destructive-ideation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/destructive-ideation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00049 | $0.00799 |
| Opus 5.5 | $0.00020 | $0.00320 |
| Sonnet 5.5 | $0.00010 | $0.00160 |
| Haiku 4.5 | $0.00005 | $0.00080 |
Grade A, and why
destructive-ideation 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 1mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
destructive-ideation
Purpose
Break fixation with explicit provocation modes, then extract constructive movement and candidate directions.
Input contract
mode_contracts:
reverse: &destructive_input
required: [current_frame, target_problem]
optional: [load_bearing_assumptions, constraints]
constraints: [provocation_must_name_the_frame_or_assumption_it_attacks]
negation: *destructive_input
random-entry: *destructive_input
extreme-constraint: *destructive_input
sacred-cow: *destructive_input
distortion: *destructive_input
Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- You MUST load skill
surface-assumptionsto surface assumptions. - You MUST load skill
generate-provocationto generate the mode-specific provocation. - You MUST load skill
extract-constructive-movementto extract constructive movement. - You MUST load skill
synthesize-ideato synthesize an idea. - You MUST load skill
build-concept-fanto expand the concept fan. If the idea now requires explicit component transformation, considerstructural-transformation. If it exposes a technical or physical contradiction, considerresolve-inventive-contradiction. Deviation: mode may be reverse, negation, random-entry, extreme-constraint, sacred-cow, or distortion; record the selected mode.
Mode branches
reverse: invert the current desired/undesired relation.negation: negate a load-bearing assumption or axiom.random-entry: introduce an explicitly recorded external/random concept.extreme-constraint: force zero-resource or boundary conditions.sacred-cow: challenge an explicitly protected convention.distortion: exaggerate, compress, or otherwise perturb a salient feature.
Output contract
mode_contracts:
reverse: &assumption_attack_output
produces: [assumption_targets, provocations, constructive_movements, idea_set]
delta_fields: [findings, hypothesis_updates, assumption_updates, decisions, recommended_jumps]
negation: *assumption_attack_output
random-entry: &provocation_output
produces: [provocations, constructive_movements, idea_set]
delta_fields: [findings, hypothesis_updates, assumption_updates, decisions, recommended_jumps]
extreme-constraint: *assumption_attack_output
sacred-cow: *assumption_attack_output
distortion: *provocation_output
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.
- 1mo ago First seen · 64 lines · 49 tokens per session scan A 653e50d6a3cd
destructive-ideation is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed 4d ago), licensed Apache-2.0. It adds 49 tokens to every session and 799 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-24.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…