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 apply-perturbationgit 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/apply-perturbation)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/apply-perturbation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/apply-perturbation/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/apply-perturbation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/apply-perturbation.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 | $0.00026 | $0.00567 |
| Opus 5.5 | $0.00010 | $0.00227 |
| Sonnet 5.5 | $0.00005 | $0.00113 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
apply-perturbation 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.
apply-perturbation
Purpose
Apply a controlled change to an assumption, factor, component, parameter, or condition and record the response.
Input contract
required: [baseline_artifact, perturbation_target, perturbation_axis, response_metric]
optional: [variation_range, removal_mode, factor_list, uncertainty_model]
constraints: [change one declared target or axis at a time unless the caller explicitly supplies an interaction design; preserve baseline comparability]
Procedure
- Record the baseline artifact, target, axis, response metric, and comparison direction.
- Generate the caller-specified variation, removal, negation, or ablation conditions.
- Re-evaluate the response at each condition and attach evidence and uncertainty.
- Identify degradation, flip points, or threshold regions and summarize the effect.
Output contract
produces: [perturbation_series, response_comparison, degradation_or_flip_points, interpretation]
delta_fields: [findings, evidence_updates, decisions, uncertainties]
Quality gates
- Controlled perturbation records performance at each point along one defined axis and identifies degradation thresholds where applicable.
- Single-factor removal retains a degradation score from 0.0 (no effect) to 1.0 (collapse) and states conclusion before/after.
- Ablation removes components one by one; do not combine removals while labeling the result single-factor.
Parameterization
The caller must provide the baseline artifact or system, perturbation target and axis, range or removal mode, response metric, factor list when needed, and degradation/flip classification rule.
Failure and counterexamples
Reject when the baseline is missing, the perturbation is not attributable, response measurements are incomparable, or a degradation score is reported without before/after reasoning.
Provenance map
- resolved: deep-insight/controlled-perturbation
- concept: creative-ideation/assumption-perturbation
- resolved: creative-ideation/ablation-execution
- resolved: stress-test/single-factor-removal
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 · 26 tokens per session scan A 7df6911ad874
apply-perturbation 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 26 tokens to every session and 567 once invoked, about $0.0001 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.
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