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 audit-convergence-independencegit 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/audit-convergence-independence)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/audit-convergence-independence"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/audit-convergence-independence/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/audit-convergence-independence"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/audit-convergence-independence.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 | $0.00047 | $0.00687 |
| Opus 5.5 | $0.00019 | $0.00275 |
| Sonnet 5.5 | $0.00009 | $0.00137 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
audit-convergence-independence 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 28d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
audit-convergence-independence
Purpose
Estimate how much nominally independent convergence remains after shared priors, data, models, prompts, framings, assumptions, and upstream evidence are discounted.
Input contract
mode_contracts:
evidence-paths: &convergence_audit_input
required: [evidence_paths, claims, provenance_records]
optional: [dependency_schema, correlation_estimates]
constraints: [each_path_must_be_traceable_to_its_inputs_and_assumptions]
agents: *convergence_audit_input
models: *convergence_audit_input
methods: *convergence_audit_input
Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- You MUST load skill
identify-shared-priorsto enumerate paths, provenance, and shared priors. - You MUST load skill
verify-evidence-independenceto verify independence and mark shared dependencies. - You MUST load skill
estimate-effective-evidence-countto estimate the effective evidence count. You MUST load skillassess-sensitivityto perturb dependence assumptions. Deviation: use qualitative dependence classes when numeric correlation is unavailable; never count nominal paths as independent by default.
Output contract
mode_contracts:
evidence-paths: &convergence_audit_output
produces: [independence_ledger, effective_evidence_count, common_cause_framing, independent_path_result_or_design, correlated_errors, corrected_confidence_statement]
delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
agents: *convergence_audit_output
models: *convergence_audit_output
methods: *convergence_audit_output
Thresholds and quality gates
- A-class sufficiency: declared universe = all claimed evidence/reasoning paths; numerator = paths with complete provenance and independence assessment; batch increment = one newly traced path; stopping reason = effective count stabilizes or remaining paths are dependent/irrelevant; source references = path IDs, source IDs, model/prompt IDs; direction/threshold reason = lower effective count when shared dependencies increase.
- Report nominal N and N_eff separately.
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.
- 28d ago First seen · 56 lines · 47 tokens per session scan A de9197cc0436
audit-convergence-independence is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed yesterday), licensed Apache-2.0. It adds 47 tokens to every session and 687 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.
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