Agent skill

Analyze Constraints Readiness

by yogsoth-ai in yogsoth-ai/de-anthropocentric-research-engine

Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.

Apache-2.0Auto-check passedLegal & Compliance

Install Analyze Constraints Readiness

skills CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyze-constraints-readiness .claude/skills/analyze-constraints-readiness && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analyze-constraints-readiness
GitHub stars
505
Token cost
~3.6k tokens
SKILL.md length
1,375 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Apache-2.0

At a glance

Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.

  • Works in 4 steps: Define candidate, dimensions, hard… → Select obstacle-triage,… → You MUST load skill score-object to… → …
  • Tasks that involve Audit readiness
  • SKILL.md covers Purpose, Input contract, Execution protocol and Mode branches, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analyze Constraints Readiness is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. Depth selects lightweight triage, readiness assessment, or causal/TOC-style constraint analysis.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Legal & Compliance, covering Audit readiness. The repository describes itself as: A 267-skill research graph in pure markdown — 51 research operations built from 216 single-purpose steps, composed in any order with explicit backtracking. One npx install, no… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Audit readiness

Example prompts

  • “/analyze-constraints-readiness”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Define candidate, dimensions, hard constraints, and target gates. You MUST load skill classify-constraint to classify each declared…
  2. Select obstacle-triage, readiness-assessment, resource-envelope, causal-constraint-analysis, or maturation-path.
  3. You MUST load skill score-object to score the selected dimensions with evidence. You MUST load skill identify-bottleneck to identify…
  4. You MUST load skill assess-removability to test whether binding constraints can be removed. You MUST load skill design-mitigation to…

What it can do on your machine

Read from SKILL.md and the folder at commit bdb3524. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyze Constraints Readiness loads about 3.6k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 1,375 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yogsoth-ai/de-anthropocentric-research-engine at commit bdb3524, republished under its Apache-2.0 licence (© yogsoth-ai). 1,375 words, ~3,649 tokens.

Download SKILL.mdSave it as .claude/skills/analyze-constraints-readiness/SKILL.md (or your agent's skills folder).
name
analyze-constraints-readiness
description
Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. Depth selects lightweight triage, readiness assessment, or causal/TOC-style constraint analysis.

analyze-constraints-readiness

Purpose

Assess feasibility and readiness by identifying constraints, resources, dependencies, bottlenecks, and maturation gates.

Input contract

yaml
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.

  1. Define candidate, dimensions, hard constraints, and target gates. You MUST load skill classify-constraint to classify each declared constraint.
  2. Select obstacle-triage, readiness-assessment, resource-envelope, causal-constraint-analysis, or maturation-path.
  3. You MUST load skill score-object to score the selected dimensions with evidence. You MUST load skill identify-bottleneck to identify binding constraints and dependencies.
  4. You MUST load skill assess-removability to test whether binding constraints can be removed. You MUST load skill design-mitigation to design removal or mitigation paths and return a readiness conclusion. If several feasible responses must be balanced as a joint set, consider portfolio-optimization. If the target goal remains too broad to assess, consider decompose-research-goal. If external change dominates present readiness, consider analyze-future-scenarios. If several candidate paths are ready for comparative selection, rank-candidates may 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 skill identify-obstacles to enumerate the obstacles. You MUST load skill list-undesirable-effects to 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 skill assess-readiness-dimension to assess every required dimension.
  • resource-envelope: estimate time, cost, and personnel bounds from analogies, then flag low-confidence estimates for investigation. You MUST load skill quantify-resource-gap to quantify the gap. You MUST load skill identify-critical-chain to 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 skill trace-causal-chain to trace constraint propagation. You MUST load skill extract-core-conflict to isolate the core conflict. You MUST load skill challenge-assumption to 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 skill project-future-reality to project the proposed path. You MUST load skill apply-stage-gate to apply its stage gates.

Output contract

yaml
mode_contracts:
  obstacle-triage: &constraint_output
    produces: [constraint_register, bottlenecks, mitigation_paths]
    delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
  readiness-assessment:
    produces: [readiness_profile, bottlenecks]
    delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
  resource-envelope:
    produces: [resource_envelope, bottlenecks, mitigation_paths]
    delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
  causal-constraint-analysis: *constraint_output
  maturation-path:
    produces: [readiness_profile, resource_envelope, stage_gates, mitigation_paths]
    delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]

Thresholds and quality gates

  • Feasibility, maturity, constraint, resource, and maturation gates use declared dimension/evidence/constraint coverage ratios; record numerator, denominator, batch increment, stopping reason, and source references.

  • Preserve structural requirements: at least one hard constraint, one removal path per removable constraint, explicit stage gates, and a binding-constraint rule relative to the observed score distribution.

  • Feasibility dimensions >=5; blockers >=3 per candidate where source protocol applies.

  • Maturity diagnosis: >=5 dimensions, >=2 evidence items per dimension, >=1 bottleneck.

  • Constraint identification: >=3 constraints per candidate; >=1 hard constraint; >=1 removal path per removable constraint.

  • Resource envelope: >=3 dimensions (time, cost, personnel) and >=2 analogies per estimate.

  • Maturation path: >=3 stage gates and >=2 milestones per stage.

  • Binding constraint threshold: sensitivity score >2* median.

Failure and counterexamples

Do not label a candidate ready with missing evidence, unclassified hard constraints, or an unbounded resource estimate. A conflict with no manageable injection remains blocked.

Provenance map

26 architecture old entries; readiness, feasibility, resource, obstacle, dependency, sensitivity, and maturation families are merged by mode. Missing aliases are listed in log.

Legacy context checkpoint / Delta notes

Append dimension scores/evidence, constraint IDs, bottleneck rationale, resources, gates, and unresolved conflicts.

Preserved source criteria ledger

sourcesource linekindsource criterion
feasibility-assessment42numeric-table\
feasibility-assessment75numeric\
feasibility-assessment76numeric\
feasibility-assessment77numeric\
feasibility-assessment78numeric\
maturity-diagnosis23numeric\
maturity-diagnosis24numeric\
maturity-diagnosis25numeric\
maturity-diagnosis53textual1. Identify relevant dimensions for the candidate (minimum: technical, market, regulatory, resource, organizational)
maturity-diagnosis64numericoverall_readiness: <1-9 TRL scale>
constraint-identification23numeric\
constraint-identification24numeric\
constraint-identification25numeric\
constraint-identification58numeric4. For constraints with removability score > 0.3, design removal-path
resource-envelope-estimation24numeric\
resource-envelope-estimation25numeric\
resource-envelope-estimation26numeric\
resource-envelope-estimation58numeric3. Identify >= 2 analogous projects and extract their actual resource consumption
resource-envelope-estimation61numeric6. Flag any estimates with confidence < 0.5 for further investigation
comparative-feasibility-ranking16textualPurpose: Produce a defensible ranking of candidates by feasibility. Uses multi-dimensional radar charts to visualize relative strengths and a weighted feasibility index to collapse multiple dimensions into a single comparable score.
comparative-feasibility-ranking27numeric\
comparative-feasibility-ranking28numeric\
comparative-feasibility-ranking29numeric-table\
comparative-feasibility-ranking58numeric2. Normalize scores to a common scale (1-9 recommended)
maturation-pathway-design27numeric\
maturation-pathway-design28numeric\
maturation-pathway-design29numeric-table\
maturation-pathway-design37textual\
maturation-pathway-design62textual2. Define target readiness required for implementation
maturation-pathway-design76textualtarget_readiness: <required score>
multi-dimensional-readiness-scan23textual3. Bottleneck Identification - Analyze the radar for dimensions significantly below the mean or below required thresholds. Deploy bottleneck-identification SOP on the radar data.
multi-dimensional-readiness-scan29numeric-table\
multi-dimensional-readiness-scan30numeric-table\
multi-dimensional-readiness-scan31numeric-table\
multi-dimensional-readiness-scan39numeric- Each dimension should have at least 2 evidence items supporting the score
multi-dimensional-readiness-scan41textual## Minimum Yield
multi-dimensional-readiness-scan43numeric- Complete radar with >= 5 dimensions scored
constraint-drilling26numeric4. Removal Path Design - For constraints with removability > 0.3, design concrete steps to remove or mitigate them. Deploy removal-path SOP for each removable constraint.
constraint-drilling32numeric-table\
constraint-drilling33numeric-table\
constraint-drilling34numeric-table\
constraint-drilling35numeric-table\
constraint-drilling42numeric- Stage 4 only runs for constraints with removability score > 0.3
constraint-drilling45textual## Minimum Yield
constraint-drilling47numeric- Classified constraint list with >= 3 constraints identified
constraint-drilling49numeric- Removal paths for all constraints scoring removability > 0.3
staged-gate-evaluation19textual1. Gate Criteria Definition - Define what must be true for a candidate to pass each gate. Deploy gate-criteria-definition SOP for each stage gate.
staged-gate-evaluation29numeric-table\
staged-gate-evaluation30numeric-table\
staged-gate-evaluation31numeric-table\
staged-gate-evaluation35numeric- Stage 1 should define >= 3 gates (e.g., concept feasibility, technical feasibility, implementation readiness)
staged-gate-evaluation42textual## Minimum Yield
constraint-analysis44textual## HARD-GATE
constraint-analysis46textualBefore entering this campaign, the following must be true:
constraint-analysis78textual## Budget Gate
constraint-analysis94textual## Minimum Yield
constraint-analysis97numeric- At least 1 binding constraint identified and characterized
constraint-analysis100numeric- No unresolved conflicts between top-3 constraints
resource-constraint63textual## Budget Gate
assumption-constraint55numeric- Top-5 fragile assumptions with validation paths
assumption-constraint58textual## Budget Gate
dependency-constraint60textual## Budget Gate
conflict-resolution66textual## Budget Gate
constraint-tree-building25textual- Minimum 5 UDEs for a meaningful tree
constraint-tree-building42numeric- When to escalate: If >10 UDEs found, prioritize top-5 by severity before tracing
constraint-tree-building43textual- Quality gate: Every causal link must have a BECAUSE clause (the underlying assumption)
sensitivity-ranking25textual- Express gaps in comparable units where possible
sensitivity-ranking43numeric- When to skip: If only 1-2 constraints exist, ranking is trivial
sensitivity-ranking44numeric- Threshold: Constraints with sensitivity score >2* the median are "binding"
constraint-breaking26textual- If constraint is not a dilemma, reframe: "We need X" vs "We cannot have X because Y"
constraint-breaking29numeric- Input: all assumptions from the EC (typically 8-15 assumptions across 4 arrows)
constraint-breaking35textual- Injection must be: specific, actionable, within our control, and testable
constraint-breaking36numeric- Generate 2-3 candidate injections
constraint-breaking43textual- What conditions (prerequisites) must hold?
Show full SKILL.md (34 more words)Show less

Context checkpoint / Delta notes

Append dimension scores/evidence, constraint IDs, bottleneck rationale, resources, gates, and unresolved conflicts. | constraint-breaking | 54 | numeric | - Success criterion: At least one injection that resolves the conflict with <=2 manageable side effects |

© yogsoth-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/analyze-constraints-readiness of yogsoth-ai/de-anthropocentric-research-engine.

Open the folder on GitHubat commit bdb3524

Compare with similar skills

Analyze Constraints Readiness next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analyze Constraints Readiness compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analyze Constraints Readiness this skillyogsoth-ai/de-anthropocentric-research-engine505—~3.6kAutomated safety check: PassApache-2.0
HIPAA Safe Harbor Coverage Auditmaziyarpanahi/openmed5.5k—~1.7kAutomated safety check: PassApache-2.0
ISO Standards Readiness EvidenceK-Dense-AI/scientific-agent-skills48k1 repos~4.6kAutomated safety check: NotesMIT
Iso42001Sushegaad/Claude-Skills-Governance-Risk-and-Compliance9461 repos~3.7kAutomated safety check: PassMIT
Fleet Triagegoogle-labs-code/jules-sdk137—~1.2kAutomated safety check: PassApache-2.0
PCI DSS Compliancewshobson/agents40k11 repos~1.9kAutomated safety check: PassMIT

Similar skills

  • Checks OpenMed de-identified clinical text against the 18 HIPAA Safe Harbor identifier categories and reports gaps and residual re-identification risk.

    5.5k GitHub stars~1.7k tokensUpdated today
    Legal & ComplianceAuto-check passed
  • ISO Standards Readiness Evidence

    K-Dense-AI/scientific-agent-skills

    Organizes scope, controlled documents, risk files and traceability into draft evidence for human review against ISO 13485, 14971, 17025 and 15189.

    48k GitHub starsUsed in 1 repo~4.6k tokens
    Legal & ComplianceAuto-check: notes
  • Iso42001

    Sushegaad/Claude-Skills-Governance-Risk-and-Compliance

    Expert ISO 42001 AI Management System (AIMS) compliance advisor.

    946 GitHub starsUsed in 1 repo~3.7k tokens
    Legal & ComplianceAuto-check passed
  • Fleet Triage

    google-labs-code/jules-sdk

    Official

    Cognitive triage of fleet audit findings. An agent skill from google-labs-code/jules-sdk.

    137 GitHub stars~1.2k tokensUpdated 2 mo ago
    Legal & ComplianceAuto-check passed
  • PCI DSS Compliance

    wshobson/agents

    Reference for building payment systems that meet PCI DSS: the 12 requirements, merchant levels, data that must never be stored, tokenization and encryption.

    40k GitHub starsUsed in 11 repos~1.9k tokens
    Legal & ComplianceAuto-check passed
  • Trust Center Builder

    GRCEngClub/claude-grc-engineering

    Builds and deploys a serverless trust center that publishes a company's compliance posture, with gated access to audit reports and an admin dashboard.

    419 GitHub stars~2.6k tokensUpdated 7 days ago
    Legal & ComplianceAuto-check passed

More from yogsoth-ai/de-anthropocentric-research-engine

All 12 skills in this repo
  • Evaluate Scenario Impact

    yogsoth-ai/de-anthropocentric-research-engine

    Evaluate a fixed candidate, research path, or portfolio under one explicit scenario using stable criteria and return impact, tradeoffs, and failure triggers.

    505 GitHub stars~465 tokensUpdated 12 days ago
    Auto-check passed
  • Evaluate Scenario Robustness

    yogsoth-ai/de-anthropocentric-research-engine

    Aggregate a candidate, strategy, or portfolio across explicit scenarios under a declared robust-decision rule such as worst-case score, minimax regret, maximin, threshold survival, or pivot-trigger…

    505 GitHub stars~478 tokensUpdated 12 days ago
    Auto-check passed
  • Evaluate Optionality

    yogsoth-ai/de-anthropocentric-research-engine

    Evaluate the value of staging, deferral, reversible commitment, and information-gathering options under uncertainty; return decision-relevant option value and trigger conditions.

    505 GitHub stars~424 tokensUpdated 12 days ago
    Auto-check passed
  • Adjust Abstraction Scope

    yogsoth-ai/de-anthropocentric-research-engine

    Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system boundary) until the representation has useful…

    505 GitHub stars~584 tokensUpdated 12 days ago
    Auto-check passed
  • Adversarial Deliberation

    yogsoth-ai/de-anthropocentric-research-engine

    Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner.

    505 GitHub stars~1.3k tokensUpdated 12 days ago
    Auto-check passed
  • Aggregate Ranking

    yogsoth-ai/de-anthropocentric-research-engine

    Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.

    505 GitHub stars~561 tokensUpdated 12 days ago
    Auto-check passed

Questions about Analyze Constraints Readiness

What does Analyze Constraints Readiness do?

Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. Analyze Constraints Readiness is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.

When should I use Analyze Constraints Readiness?

Analyze Constraints Readiness fits situations like: tasks that involve Audit readiness.

How do I install Analyze Constraints Readiness in Claude Code?

Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a claude-code`. Or copy the skill folder (skills/analyze-constraints-readiness in yogsoth-ai/de-anthropocentric-research-engine) into .claude/skills/analyze-constraints-readiness in your project. Claude Code loads it when a task matches its description.

How do I install Analyze Constraints Readiness in Codex?

Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a codex`. Or copy the skill folder (skills/analyze-constraints-readiness in yogsoth-ai/de-anthropocentric-research-engine) into .agents/skills/analyze-constraints-readiness in your project. Codex loads it when a task matches its description.

Can I use Analyze Constraints Readiness in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-constraints-readiness, .gemini/skills/analyze-constraints-readiness, .github/skills/analyze-constraints-readiness and .opencode/skills/analyze-constraints-readiness in your project.

What does Analyze Constraints Readiness need to run?

SKILL.md names no scripts, command-line tools or credentials: Analyze Constraints Readiness is instructions for the agent only.

Does Analyze Constraints Readiness access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyze Constraints Readiness safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Analyze Constraints Readiness use?

Analyze Constraints Readiness is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyze Constraints Readiness use?

About 3.6k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Analyze Constraints Readiness?

Skills that share tags, products or a category with Analyze Constraints Readiness: HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars), ISO Standards Readiness Evidence (K-Dense-AI/scientific-agent-skills, 48k stars), Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars) and Fleet Triage (google-labs-code/jules-sdk, 137 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyze Constraints Readiness?

yogsoth-ai (a GitHub organization) maintains it in yogsoth-ai/de-anthropocentric-research-engine, which has 505 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 29, 2026.

Source: yogsoth-ai/de-anthropocentric-research-engine on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.