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 analyze-constraints-readinessgit 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/analyze-constraints-readiness)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/analyze-constraints-readiness"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/analyze-constraints-readiness/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/analyze-constraints-readiness"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/analyze-constraints-readiness.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 | $0.00059 | $0.03282 |
| Opus 5.5 | $0.00024 | $0.01313 |
| Sonnet 5.5 | $0.00012 | $0.00656 |
| Haiku 4.5 | $0.00006 | $0.00328 |
Grade A, and why
analyze-constraints-readiness 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
analyze-constraints-readiness
Purpose
Assess feasibility and readiness by identifying constraints, resources, dependencies, bottlenecks, and maturation gates.
Input contract
mode_contracts:
obstacle-triage: &readiness_input
required: [candidate_or_plan, readiness_dimensions]
optional: [resource_estimates, dependencies, assumptions, target_gates]
constraints: [evidence_must_be_attached_to_each_scored_dimension]
readiness-assessment: *readiness_input
resource-envelope: *readiness_input
causal-constraint-analysis: *readiness_input
maturation-path: *readiness_input
Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- Define candidate, dimensions, hard constraints, and target gates. You MUST load skill
classify-constraintto classify each declared constraint. - Select
obstacle-triage,readiness-assessment,resource-envelope,causal-constraint-analysis, ormaturation-path. - You MUST load skill
score-objectto score the selected dimensions with evidence. You MUST load skillidentify-bottleneckto identify binding constraints and dependencies. - You MUST load skill
assess-removabilityto test whether binding constraints can be removed. You MUST load skilldesign-mitigationto design removal or mitigation paths and return a readiness conclusion. If several feasible responses must be balanced as a joint set, considerportfolio-optimization. If the target goal remains too broad to assess, considerdecompose-research-goal. If external change dominates present readiness, consideranalyze-future-scenarios. If several candidate paths are ready for comparative selection,rank-candidatesmay be the better next tactic.
Mode branches
obstacle-triage: rapidly enumerate and severity-rank the obstacles that could block the target, preserving evidence status for each one. You MUST load skillidentify-obstaclesto enumerate the obstacles. You MUST load skilllist-undesirable-effectsto retain their observed consequences.readiness-assessment: score the required readiness dimensions with supporting evidence and identify the dimensions that keep the target from being ready. You MUST load skillassess-readiness-dimensionto assess every required dimension.resource-envelope: estimate time, cost, and personnel bounds from analogies, then flag low-confidence estimates for investigation. You MUST load skillquantify-resource-gapto quantify the gap. You MUST load skillidentify-critical-chainto expose the binding resource sequence.causal-constraint-analysis: trace how constraints interact through dependencies and conflicts to identify the binding cause rather than only its symptoms. You MUST load skilltrace-causal-chainto trace constraint propagation. You MUST load skillextract-core-conflictto isolate the core conflict. You MUST load skillchallenge-assumptionto test the assumptions that sustain it.maturation-path: sequence stage gates and milestones that move the target from current readiness to the declared implementation threshold. You MUST load skillproject-future-realityto project the proposed path. You MUST load skillapply-stage-gateto apply its stage gates.
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 · 170 lines · 59 tokens per session scan A d22507a29c0d
analyze-constraints-readiness 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 59 tokens to every session and 3,282 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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