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A governed, composable library of 79 specialist skills for Thirstys Workshop. Every skill shares one constitutional baseline — provenance, uncertainty, reversibility, approval, and handoff rules — and ships as a self-contained skill.zip for ChatGPT Skills.
Skills are progressively being assessed and reconstructed under the Thirstys Skill Standard; each skill's maturity, class, version, and evaluation status are recorded in CATALOG.json. An UNASSESSED maturity means the skill predates the standard and has not yet been assessed against it — not that it is unusable.
How it works
Skill sources are small and declarative. The two constitutional reference files live once in shared/ and are injected into every package at build time, so amending the constitution is a one-file change that reaches all 79 skills on the next build.
flowchart LR
A["skills/<name>/<br/>SKILL.md + agents/"] --> B["build.ps1"]
S["shared/references/<br/>constitutional-rules.md<br/>handoff-schema.md"] --> B
B --> Z["dist/<name>/skill.zip"]
Z --> U["ChatGPT Skills upload"]
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Quick start
./build.ps1 # package all skills into dist/<name>/skill.zip
./build.ps1 -Skill <name># rebuild one skill
./build.ps1 -Clean # wipe dist/ and rebuild everything
./validate.ps1 # check structure, frontmatter, catalog, and docs sync
./new-skill.ps1-Name <name>-Description ...-Objective ...-Outputs ...
# scaffold a new skill and register it in CATALOG.json
Install by uploading one dist/<name>/skill.zip at a time in ChatGPT Skills.
Repository layout
Path
Purpose
skills/<name>/SKILL.md
The skill itself: frontmatter (name, description) plus its objective, method, output contract, quality gate, and composition guidance
skills/<name>/agents/openai.yaml
Display metadata for the ChatGPT Skills interface
skills/<name>/references/, assets/, scripts/
Optional package depth: domain references, output schemas/templates, deterministic scripts (packaged into the zip automatically)
shared/references/
Single source of truth for the constitutional rules and the inter-skill handoff schema
CATALOG.json
Machine-readable index: identity, objective, outputs, group, class, version, maturity, and validation record for every skill
library-schema.json
Canonical enums and thresholds (maturity, classes, groups, outcomes, eval minimums) consumed by all three scripts
Per-skill evaluation suites: trigger/functional/boundary cases, fixtures, and committed result records (how they work)
dist/
Build output (gitignored) — regenerate with ./build.ps1; each zip ships with a skill.zip.sha256 package-identity checksum
.github/workflows/ci.yml
CI: runs validate.ps1, check-evals.ps1 (structural only), and build.ps1 on every push and PR, publishing the zips as a build artifact
Constitutional baseline
Every skill operates under the same operating rules (shared/references/constitutional-rules.md): distinguish fact from inference, preserve provenance, never invent missing context, separate analysis from consequential action, prefer reversible moves, and end with residual uncertainty and the next highest-value action. Structured handoffs between skills follow shared/references/handoff-schema.md.
A skill may override a shared file by shipping its own copy at the same relative path — validate.ps1 flags every override so none go unnoticed.
Library standard
The Thirstys Skill Standard defines what a finished skill package contains: a capability delta (what the skill changes versus unaided execution), explicit trigger and non-trigger conditions, an input contract with minimum evidence, a specialist method, a failure taxonomy, negative space (when the skill returns a no-result outcome instead of forcing a match), an output contract, and class-appropriate evaluations. Maturity (UNASSESSED → DRAFT → EXPERIMENTAL → REVIEWED → VALIDATED → STABLE) is a summary of a per-skill validation record — structural checks, executed trigger/functional/boundary evaluations, human review, and real-use evidence are tracked as separate dimensions, and maturity may never claim more than the record shows. STABLE requires evidence of actual use; certification here means exactly structural validation plus recorded evaluations plus review — nothing cryptographic or formally verified is implied.
Resolve ambiguous project terms, select the correct context, and route requests to the right specialist skill — or return an explicit no-match outcome (AMBIGUOUS, UNSUPPORTED, INSUFFICIENT_EVIDENCE, …) instead of forcing a fit.
Inventory and classify uploaded folders, repositories, papers, notes, and archives. Use when the user asks to ingest, map, catalog, normalize, or prepare a workspace for downstream analysis.
Synthesize grounded knowledge across repositories, papers, specifications, websites, and internal documents. Use when asked for a state-of-knowledge brief, concept trace, cross-source synthesis, or gap analysis.
Coordinate Q hostile review using assumptions, epistemic status, contradictions, absent stakeholders, power, falsification, reversibility, mission drift, and attention allocation. Use when the user addresses Q or asks what they are not seeing.
Design or evaluate governed-AI constitutional systems. Use for constitutions, authority models, rights, duties, amendment processes, enforcement, appeals, and emergency powers.
Perform hostile review of constitutional and governance structures. Use when asked to attack, red-team, stress-test, capture-test, or identify abuse paths in governed systems.
Generate tests from constitutional language and governance requirements. Use for compliance, adversarial, boundary, delegation, memory, emergency, amendment, and recovery scenarios.
Stress-test constitutions through extended social and institutional scenarios such as scarcity, conflict, capability shifts, misinformation, succession, and collapse.
Compare how alternative governance structures might have handled an event. Use to test centralized, federated, delegated, or rights-based alternatives.
Run a constitutional postmortem after failure or near miss. Use to distinguish constitutional, interpretation, enforcement, evidence, authority, and oversight failures.
Audit traceability from governance principles through requirements, policies, controls, code, tests, and evidence. Use when verifying whether implementation supports stated governance claims.
Map where human, agent, institutional, and constitutional authority begins and ends. Use to find overlaps, gaps, circular escalation, and undefined sovereignty.
Trace delegated authority through principals, agents, subagents, tools, and external systems. Use to verify scope, duration, revocability, and accountability.
Evaluate why affected parties should regard a governance system as legitimate. Use for consent, participation, competence, procedure, outcomes, representation, and rights protection.
Model gradual capture of governance institutions. Use for appointment, metric, dependency, funding, data, emergency, expertise, and procedural capture scenarios.
Map actual power rather than formal authority. Use to analyze control over compute, data, deployment, funding, credentials, audits, appeals, communication, and shutdown.
Find external dependencies that can undermine independence or constitutional guarantees, including providers, hosting, identity, registries, data, funding, domains, and trust anchors.
Evaluate systems for durable human-AGI relations. Use for agency, consent, reciprocal duties, power asymmetry, representation, exit rights, conflict resolution, and moral uncertainty.
Design agreements between independently governed agents or systems. Use for recognition, jurisdiction, information exchange, noninterference, verification, breach, arbitration, and withdrawal.
Audit whether separately governed systems can interact safely. Use to find incompatible authority, identity, consent, evidence, and enforcement assumptions.
Design and audit meaningful consent and withdrawal mechanisms. Use for informed, specific, voluntary, comprehensible, revocable, time-bounded, enforceable consent.
Reconstruct consequential decisions from available evidence. Use to explain what information, rules, interpretations, tools, and interventions shaped an outcome.
Apply explicit epistemic status to meaningful claims. Use to separate observed, verified, reported, inferred, hypothesized, speculative, normative, contested, and unknown statements.
Find incompatible statements across repositories, papers, policies, conversations, and specifications. Use for contradiction, drift, and terminology conflict analysis.
Trace how an idea, term, mechanism, or policy evolved across time and artifacts. Use to locate origins, revisions, renamings, forks, and current authority.
Maintain canonical terminology across projects. Use to build glossaries, normalize terms, identify overloaded language, and deprecate ambiguous synonyms.
Identify affected but absent or unrepresented stakeholders, including future persons, nonusers, maintainers, dependent institutions, and artificial agents.
Identify what is omitted, unasked, assumed, strategically ignored, or rendered invisible in a plan, architecture, paper, or decision. Use when the user asks Q, what am I not seeing, hostile review, or challenge the framing.
Audit scholarly and technical claims for evidence, overstatement, falsifiability, citation gaps, and reproducibility. Use before submission or publication.
Coordinate manuscript and release preparation across papers, repositories, metadata, DOI, ORCID, SSRN, Zenodo, and project sites. Use when preparing work for publication.
Map current literature, prior art, and adjacent work around a concept or mechanism. Use for novelty assessment, research positioning, and terminology discovery.
Compare papers, repositories, diagrams, specifications, release notes, and public descriptions for consistency. Use to detect stale claims, terminology, or implementation drift.
Map a repository as an architectural system. Use when asked to explain components, dependencies, trust boundaries, data flows, control flows, or governance enforcement locations.
Convert research, governance, or product specifications into executable engineering plans. Use for epics, issues, interfaces, schemas, acceptance criteria, and phased implementation.
Turn discussions, experiments, and changes into durable architecture decision records. Use when recording why a choice was made and what would reverse it.
Grade a prospective collaborator, platform, or funder across six diligence dimensions on ranked dated evidence — UNKNOWN scored as risk, exit cost modeled, posture set by decision table.
Take a capability from intent to a validated, well-triggered skill package that meets the Skill Standard — or convert a procedure, standard, or checklist into one. Owns the whole authoring lifecycle as a single job.
Audit the library as a whole: coverage gaps, overlap and trigger collisions, specialization classification via the blind test, and per-skill add/deepen/merge/split/deprecate dispositions.
Run a skill's evaluation suite with the class-appropriate method, compare to baseline and prior version, and record provenance-complete results — the eval evidence maturity depends on.
Decide a skill's version bump, evidence-backed maturity transition, and release readiness, and manage deprecation with replacement pointers.
Contributing
See CONTRIBUTING.md. The short version: ./new-skill.ps1 to scaffold, edit the generated SKILL.md, add the skill to the catalog table above, then ./validate.ps1 and ./build.ps1 must both pass.
About
Thirstys Skills - a governed, composable library of 79 specialist skills for Thirstys Workshop