feat(skill): promise-theory catalog integration

Add the promise-theory skill to the repository catalog: root README entry,
regenerated llms.txt and marketplace/plugin packaging, and a
references/skill-triggers.md row.

Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>

.claude-plugin/marketplace.json

@@ -896,6 +896,15 @@
       "strict": false,
       "description": "Apply distilled coding principles from 14 classic software books to code review, refactoring, design, and implementation decisions. Do not use for language- or framework-specific tutorials, tool manuals, or tasks already governed by a project's established conventions."
     },
+    {
+      "name": "promise-theory",
+      "source": "./",
+      "skills": [
+        "./promise-theory"
+      ],
+      "strict": false,
+      "description": "Design and diagnose coordination in hybrid human + AI agent workforces using promise theory (Burgess/Bergstra): model agents as autonomous, coordination as voluntary offers plus acceptance, and trust as calibrated assessment. Use for delegation modeling, capability manifests and agent contracts, coordination-failure diagnosis, trust/verification calibration, convergent self-healing systems, and converting obligation-based designs to promise-based. Do not use for enforceable centralized control, legal contract drafting (promise theory is not contract law), simple single-agent prompting, imperative push-based orchestration, or tool manuals — route those to the tool's own skill."
+    },
     {
       "name": "pydanticai",
       "source": "./",

.codex-plugin/plugin.json

@@ -120,6 +120,7 @@
     "./product-strategy",
     "./production-readiness",
     "./programming-principles",
+    "./promise-theory",
     "./pydanticai",
     "./qa-methodology",
     "./raleigh",

README.md

@@ -411,6 +411,10 @@ Assemble cross-domain production evidence into a risk-scaled launch decision. De
 
 Distilled coding principles from 14 classic software engineering books (Clean Code, DDD, Refactoring, Release It!, DDIA, Code Complete, and more). Cross-cutting principles organized by concern, task-to-book mapping, per-book mini and full rule sets, and a structured code-assessment workflow.
 
+### [promise-theory](promise-theory/SKILL.md)
+
+Design and diagnose coordination in hybrid human + AI agent workforces using promise theory (Burgess/Bergstra): model agents as autonomous, coordination as voluntary offers plus acceptance, and trust as calibrated assessment. Covers delegation modeling, capability manifests and agent contracts, coordination-failure diagnosis, trust/verification calibration, and converting obligation-based designs to promise-based ones. Ships 7 references, 3 templates, a stdlib-only lint CLI, and 6 evals.
+
 ### [pydanticai](pydanticai/SKILL.md)
 
 Build production-grade AI agents and graph-based state machines with PydanticAI and PydanticGraph. Covers agent creation, function tools with RunContext dependencies, structured output validation, streaming (text/events/graph nodes), a 20+ capability plugin system with on-demand loading (Thinking, WebSearch, MCP, Hooks, etc.), 16 model providers with FallbackModel and concurrency limiting, multi-agent delegation and programmatic hand-off, comprehensive testing with TestModel/FunctionModel, and the PydanticEvals evaluation framework. Includes the full PydanticGraph API — both BaseNode (class-based) and GraphBuilder (function-based) with parallel map/broadcast operations, joins with reducers, decisions, Mermaid rendering, and step-by-step execution. Ships 8 reference files covering core agents, capabilities/hooks, graph, models/output, patterns/integrations, testing/evals, worked examples, and an API surface quick reference.

llms.txt

@@ -101,6 +101,7 @@
 - [production-excellence](bundles/production-excellence/SKILL.md): Route cross-domain production evidence (readiness, migration, recovery, capacity/cost, incident-learning) into a launch or operational decision — go, no-go, defer, exception, or escalation — with an accountable owner and a post-launch learning path. Compose production specialists without copying their runbooks. Do not use for incident command, release-pipeline mechanics, platform architecture, threat modeling, data-pipeline design, or any task owned end-to-end by a single specialist skill; do not use as a generic checklist detached from service ownership, risk, evidence, and verification.
 - [production-readiness](production-readiness/SKILL.md): Define the minimum production evidence packet by risk class and produce go/no-go/defer/exception launch decisions with accountable owners. Cover ownership, user/business outcome, dependencies, SLOs, observability, support, security, data, rollback, capacity, and cost — every category with a named source or explicit missing-evidence outcome. Route detailed checks to existing specialist skills. Do not use for release pipeline mechanics (release-engineering) or incident response and SLO operations (site-reliability-engineering).
 - [programming-principles](programming-principles/SKILL.md): Apply distilled coding principles from 14 classic software books to code review, refactoring, design, and implementation decisions. Do not use for language- or framework-specific tutorials, tool manuals, or tasks already governed by a project's established conventions.
+- [promise-theory](promise-theory/SKILL.md): Design and diagnose coordination in hybrid human + AI agent workforces using promise theory (Burgess/Bergstra): model agents as autonomous, coordination as voluntary offers plus acceptance, and trust as calibrated assessment. Use for delegation modeling, capability manifests and agent contracts, coordination-failure diagnosis, trust/verification calibration, convergent self-healing systems, and converting obligation-based designs to promise-based. Do not use for enforceable centralized control, legal contract drafting (promise theory is not contract law), simple single-agent prompting, imperative push-based orchestration, or tool manuals — route those to the tool's own skill.
 - [pydanticai](pydanticai/SKILL.md): Build type-safe AI agents and graph-based workflows with PydanticAI and PydanticGraph. Agent creation, function tools, capabilities, dependency injection, structured output, streaming, multi-agent patterns, testing, evals, and graph state machines. Use whenever you are building agents, tool-using LLM workflows, or graph-based state machines in Python.
 - [qa-methodology](qa-methodology/SKILL.md): Design and apply QA methodology for software teams: test strategy, regression testing, CI failure triage, test automation, quality gates and metrics, risk-based testing, exploratory testing, test design techniques, AI code quality gates (independent verification, acceptance-criteria testability review for agentic Spec-Driven Development), mutation-guided test hardening and review evidence (surviving mutants, weak assertions, diff-aware mutation testing), agentic eval design (dataset test design, judge-as-system-under-test, flaky-eval discipline), QA career levels (Senior/Staff/Principal), and SDET engineering (test infrastructure, gTAA, CI/CD integration). Do not use for root-cause debugging of production incidents, security implementation or threat modeling, or evaluation framework governance and statistical analysis — route those to systematic-debugging, secure-software-engineering, and agent-evals-and-observability respectively.
 - [raleigh](raleigh/SKILL.md): Query, search, and download public datasets and civic information for the City of Raleigh. Use for live ArcGIS Hub catalog discovery, ArcGIS FeatureServer and MapServer queries, ImageServer imagery exports, official Raleigh geocoding, GoRaleigh transit feeds, guest-public development records, public RaleighNC.gov content, eSCRIBE public meetings, Raleigh fire reports and inspections, and the Raleigh-Wake ECC active incident feed. Do not use for private data, authenticated operations, payments, submissions, bulk crawling, or non-public portals.

references/skill-triggers.md

@@ -111,3 +111,4 @@ Each skill's `description` field is the canonical routing contract. This conveni
 | "HubSpot", "CRM", "contact lookup", "deal pipeline", "pipeline view", "move a deal", "crm-cli", "HubSpot contact" | [crm](../crm/SKILL.md) |
 | "Stripe", "account balance", "payment intent", "subscription", "cancel subscription", "stripe-cli", "Stripe payments", "payment status" | [stripe](../stripe/SKILL.md) |
 | "mental health", "DSM", "DSM-5", "DSM-5-TR", "psychiatric symptoms", "symptoms could be", "diagnostic criteria", "mental health condition", "neurocognitive condition", "neurological condition", "differential diagnosis", "explain a diagnosis", "questions for my clinician", "questions for my therapist", "delirium vs dementia", "ADHD vs anxiety" | [dsm5](../dsm5/SKILL.md) |
+| "promise-theory", "promise theory", "promises" | [promise-theory](../promise-theory/SKILL.md) |