ai-literacy-superpowers

Plugin ai-literacy-superpowers from marketplace ai-literacy-superpowers in Habitat-Thinking/ai-literacy-superpowers. Commands read from the repo's manifest — 3 days ago.

Skills (41)

• advocatus-diaboli

  Use when acting as the adversarial spec reviewer — raises steel-manned objections across six categories before plan approval, requires evidence per objection, and discloses what was not challenged

• ai-literacy-assessment

  This skill should be used when the user asks to "assess AI literacy", "run an assessment", "check literacy level", "evaluate our AI collaboration", "where are we on the framework", or wants to determine their team's AI literacy level using the ALCI instrument.

• auto-enforcer-action

  Use when setting up automatic PR constraint enforcement via GitHub Actions — covers the advisory-vs-blocking split, workflow installation, configuration options, and reading the output

• carpaccio

  Use when acting as the cadence governor — slices a raw task description into thin, end-to-end-complete pieces before any spec is written; produces a structured slicing record for human disposition; runs at orchestrator step 0

• choice-cartographer

  Use when acting as the decision-archaeology agent — surfaces decisions a spec has made (including the silent ones), emits each material choice as a Henney-style pattern story for human disposition, and pays down intent debt before plan approval

• coda

  Use when closing an agentic session deliberately rather than by attrition — carries the four-step ritual (survey, park, closure summary and reflection, close), the anchor grammar behind the next-action question, the evidence for why a specific written plan releases an unfinished thread, and the anti

• cognitive-reservoir

  Use when watching the human verifier rather than the output — defines the observable proxies, the observed/inferred/asked confidence discipline, the default thresholds, the one firm principle, six-level scaling, and the honesty rule that the reservoir-warden agent and the reservoir-check Stop hook b

• component-design-with-tdad

  Use when designing a new plugin component (skill, agent, command, or backing script) for the ai-literacy-superpowers plugin or a sister plugin in this marketplace. Surfaces the design questions that the four-layer TDAD architecture implies — component type, tier targeting, scenario shape, FINDING-vs

• constraint-design

  This skill should be used when the user asks to "add a constraint", "design a constraint", "write a harness rule", "choose enforcement type", "promote a constraint", "configure a verification slot", or needs guidance on the Constraints section of HARNESS.md.

• context-engineering

  This skill should be used when the user asks about "writing conventions", "codebase context", "HARNESS.md context section", "convention documentation", "how to write enforceable rules", or needs guidance on the Context section of HARNESS.md.

• convener

  Use when mapping the voices a spec affects and drafting the concrete question worth asking each one — the charter, the line the agent never crosses, where voices come from, what makes a question worth asking rather than a meeting worth scheduling, the three-way Routing Rule, and the consultation-rec

• convention-extraction

  Use when setting up a new project's conventions, onboarding AI to an existing codebase, after team composition changes, or when AI output quality varies depending on who prompts — guides structured discovery of tacit team knowledge into explicit, enforceable artefacts

• convention-sync

  Use when syncing HARNESS.md conventions to Cursor, Copilot, and Windsurf convention files — reads Context and Constraints sections and generates tool-specific output so all AI coding tools share the same project rules

• cost-estimation

  Use when the user wants to estimate or predict the cost, token usage, or time of a task BEFORE it runs — "how much will this feature cost to build", "estimate the tokens for this spec", "what will this slice cost", "predict the agent-compute time before I commit" — produces a token + time estimate a

• cost-tracking

  Use when the user wants to capture AI tool costs, review spending trends, set cost budgets, or integrate cost data into health snapshots — guides quarterly cost capture, records data in a structured format, and updates MODEL_ROUTING.md with observed cost patterns

• cross-repo-orchestration

  Use when coordinating changes across multiple repositories — syncing skills, templates, agents, or harness policies between upstream and downstream repos, or designing portfolio-level agent orchestration

• cupid-code-review

  Use when reviewing or refactoring code and wanting a structured lens beyond SOLID — applies Daniel Terhorst-North's CUPID properties to surface improvement opportunities in any codebase or language.

• dependency-vulnerability-audit

  Use when auditing project dependencies for known vulnerabilities, supply chain risk, or provenance issues — covers Go modules, Maven/JVM, and CI integration for automated scanning

• docker-scout-audit

  Use when auditing Docker images in this project for CVEs, base image staleness, or remediation recommendations — covers all four TUI images (Go, Python, Kotlin, C#)

• dynamic-workflows

  This skill should be used when an agent is deciding whether to author a dynamic workflow — a self-authored, ephemeral multi-agent harness — for a task. Use when the user asks about "dynamic workflows", "multi-agent harness", "fan-out", "subagents in parallel", "adversarial verification", "the ultrac

• fitness-functions

  Use when designing architectural fitness functions as GC rules — periodic checks that verify system-wide properties like layer boundaries, coupling trends, and complexity hotspots, complementing per-change constraints with weekly architectural health monitoring

• garbage-collection

  This skill should be used when the user asks about "garbage collection rules", "entropy fighting", "documentation staleness", "dead code detection", "convention drift", "periodic checks", "auto-fix rules", or needs guidance on the Garbage Collection section of HARNESS.md.

• github-actions-supply-chain

  Use when reviewing GitHub Actions workflow files for security issues, hardening CI pipelines, or assessing supply chain risk in a repository that uses GitHub Actions

• governance-audit-practice

  Use when conducting a governance audit — detecting semantic drift in governance constraints, inventorying governance debt, checking three-frame alignment, or when the governance-auditor agent needs methodology for deep investigation.

• governance-constraint-design

  Use when writing governance constraints for HARNESS.md, translating governance language into operational meaning, reviewing existing governance constraints for falsifiability, or when "/governance-constrain" needs guidance on the authoring workflow.

• governance-observability

  Use when defining governance metrics, reading governance health snapshots, generating the governance dashboard, or understanding the governance data model. Referenced by the governance-auditor agent and the /governance-health command.

• harness-audit-engine

  Use when running the shared drift-detection logic that backs /harness-audit and /harness-sync — produces a structured drift report covering convention files, ONBOARDING.md, snapshot staleness, constraint regressions, recurring reflection patterns, and HARNESS.md Status section accuracy.

• harness-engineering

  This skill should be used when the user asks about "harness engineering", "what is a harness", "harness framework", "AI code quality", "context engineering", "architectural constraints", "garbage collection for code", or wants to understand the conceptual foundation behind the harness-engineering pl

• harness-observability
• harness-onboarding
• literacy-improvements
• literate-programming
• mast
• model-sovereignty
• portfolio-assessment
• portfolio-dashboard
• secrets-detection
• sentinel-design
• team-api
• verification-slots
• wip-warden

Slash commands (32)

• /ai-literacy-superpowers:assess

  Run an AI literacy assessment — scan the repo for evidence, ask clarifying questions, produce a timestamped assessment document, apply immediate habitat fixes, recommend workflow changes, capture a reflection, and add a literacy level badge to the README

• /ai-literacy-superpowers:carpaccio

  Run the carpaccio agent (cadence governor) on a task description — produces a slicing record at docs/superpowers/slices/<task-slug>.md; use at orchestrator step 0 or before spec-writer when running manually

• /ai-literacy-superpowers:choice-cartograph

  Run the Choice Cartographer (decision-archaeology agent) on a spec — produces the choice-story record at docs/superpowers/stories/<slug>.md; use after spec-mode /diaboli dispositions are resolved, before plan approval

• /ai-literacy-superpowers:coda

  Close a session deliberately — survey what landed and what is still live, park each open thread with a concrete next action, write the closure summary through /reflect, and end. Dispatches the read-only coda agent and persists what it returns after you confirm.

• /ai-literacy-superpowers:convene

  Run the Convener on a spec — maps the roles and groups it affects, drafts the concrete question worth asking each one, and writes the consultation record at docs/superpowers/consultations/<slug>.md; never contacts anyone; use at plan approval alongside /choice-cartograph

• /ai-literacy-superpowers:convention-sync

  Sync HARNESS.md conventions to Cursor, Copilot, and Windsurf convention files

• /ai-literacy-superpowers:cost-capture

  Capture AI tool cost data — guide through provider dashboards, record spend and token usage, compare to previous snapshot, update MODEL_ROUTING.md

• /ai-literacy-superpowers:cost-estimate

  Estimate a target's tokens, agent-compute time, and (when grounded) cost before it runs — the prospective sibling of /cost-capture. Dispatches the read-only cost-estimator agent, validates the returned record, and writes it after you dispose.

• /ai-literacy-superpowers:diaboli

  Run the adversarial reviewer on a spec or implementation — produces the objection record at docs/superpowers/objections/<slug>.md (spec mode) or <slug>-code.md (code mode); use after spec-writer completes or after the final code-reviewer PASS

• /ai-literacy-superpowers:extract-conventions

  Run a guided convention extraction session — surfaces tacit team knowledge through structured questions and maps answers to CLAUDE.md conventions and HARNESS.md constraints

• /ai-literacy-superpowers:governance-audit

  Run a deep governance investigation — semantic drift analysis, governance debt inventory, constraint falsifiability scoring, three-frame alignment checks, and governance health reporting

• /ai-literacy-superpowers:governance-constrain

  Guided authoring of governance constraints — translates governance language into operational meaning with three-frame alignment check, then writes the constraint to HARNESS.md

• /ai-literacy-superpowers:governance-health

  Show governance health snapshot — constraint count, falsifiability ratio, drift score, debt inventory, last audit date. Pass --dashboard to generate the HTML governance dashboard.

• /ai-literacy-superpowers:harness-affordance

  Manage the project's affordance inventory — declared tools the agent can invoke, the identity each tool runs under, and the audit trail each tool produces. Subcommands - discover (scan config to produce a draft inventory), add (promote a draft into HARNESS.md with governance metadata), review (re-va

• /ai-literacy-superpowers:harness-audit

  Run a full meta-verification of the harness — check whether HARNESS.md matches reality and update the status

• /ai-literacy-superpowers:harness-constrain

  Add a new constraint to HARNESS.md or promote an existing one from unverified to agent or deterministic

• /ai-literacy-superpowers:harness-gc

  Manage and run garbage collection rules — add new periodic checks or run existing ones on demand

• /ai-literacy-superpowers:harness-health

  Generate a harness health snapshot — enforcement status, mutation trends, learning velocity, cadence compliance, and meta-observability checks

• /ai-literacy-superpowers:harness-init

  Set up a living harness for this project — select features, discover the stack, define conventions, generate HARNESS.md with enforcement. Re-run to add features incrementally.

• /ai-literacy-superpowers:harness-onboarding

  Generate a human-readable onboarding document from HARNESS.md, AGENTS.md, and REFLECTION_LOG.md — a friendly guide for new team members

• /ai-literacy-superpowers:harness-status

  Show the current health of the project's harness — enforcement ratio, drift, and garbage collection state

• /ai-literacy-superpowers:harness-sync

  Detect drift across all push-direction control surfaces, present the full picture, and apply the user's selected fixes via the existing primitives — single human-instigated entry point for keeping convention files in sync with HARNESS.md. ONBOARDING.md staleness is surfaced but not auto-fixed; users

• /ai-literacy-superpowers:harness-upgrade

  Discover and adopt new template content after a plugin upgrade — diffs your HARNESS.md against the current template and presents new items for review

• /ai-literacy-superpowers:mast

  Read the pact you set for yourself, or author one. Read mode recites your declared budget and says where you stand against it, with each key flagged for what can honestly be seen. Tune mode is the only sanctioned path that creates or amends the pact file.

• /ai-literacy-superpowers:observatory-verify

  Verify that all data signals the Habitat Observatory expects are present and correctly formatted — runs the 81-signal checklist against the latest output files

• /ai-literacy-superpowers:portfolio-assess

  Assess AI literacy across multiple repositories — aggregate assessments into a portfolio view with level distribution, shared gaps, and prioritised improvements

• /ai-literacy-superpowers:reflect

  Capture a reflection after completing work — what was surprising, what should future agents know, what could improve

• /ai-literacy-superpowers:reservoir

  Watch the human verifier the harness cannot verify — Read mode dispatches the reservoir-warden agent for a fuller cognitive-reservoir read; Tune mode helps you edit the HARNESS.md Cognitive reservoir block (thresholds and chronotype), proposing edits for you to confirm

• /ai-literacy-superpowers:superpowers-init

  Set up the complete AI Literacy framework habitat for this project — discover the stack, define conventions, scaffold harness, agent team, compound learning, and CI templates

• /ai-literacy-superpowers:superpowers-status

  Show the complete health of the project's AI Literacy habitat — harness enforcement, agent team, compound learning, model routing, and CI status

• /ai-literacy-superpowers:wip

  Count live sessions against the limit you declared for yourself — how many, which ones, and how long since each last took a turn. Counts sessions and never watches you; never invents a limit you did not set.

• /ai-literacy-superpowers:worktree

  Manage git worktrees for parallel agent isolation — spin up a new worktree, merge it back, or clean it up

Subagents (20)

• advocatus-diaboli

  Use after spec-writer completes (spec mode) or after the final code-reviewer PASS (code mode) — reads the spec or implementation and produces a structured objection record; read-only trust boundary enforces the human-cognition gate on dispositions at both gates

• assessor

  Use this agent to run an AI literacy assessment — scans the repository for observable evidence, asks clarifying questions, and produces a timestamped assessment document with a README badge. Examples: <example> Context: User wants to know their team's AI literacy level user: "Where are we on the AI

• carpaccio

  Use when starting any new task via the orchestrator — reads the raw task description, slices it into end-to-end-complete pieces, and produces a structured slicing record; read-only trust boundary enforces the human-cognition gate on dispositions; runs at orchestrator step 0 before spec-writer

• choice-cartographer

  Use after spec-mode advocatus-diaboli dispositions are resolved and before plan approval — reads the spec, reconstructs the decisions it implies (including the silent ones), and produces a structured choice-story record; read-only trust boundary enforces the human-cognition gate on dispositions

• coda

  Use at session close via /coda — surveys what landed and what is still live, proposes a thread grouping for the human to confirm, and returns parking-record content with a concrete next action per thread; read-only by design, it writes nothing and never decides that a session should end

• code-reviewer

  Use after implementation is complete and tests are green — reviews code through the CUPID and literate programming lenses, returns PASS or a prioritised list of findings

• convener

  Use at plan approval, after spec-mode advocatus-diaboli dispositions are resolved and alongside the choice-cartographer — reads the spec, maps the roles and groups it affects, drafts the one concrete question worth asking each of them, and produces a structured consultation record; never contacts an

• cost-estimator

  Use to estimate the token usage, agent-compute time, and (only when a cost snapshot grounds it) the dollar cost of a task BEFORE it runs — given a target (raw task text, a slicing record, a single slice, or a spec), reads MODEL_ROUTING.md and the latest observability/costs/ snapshot, applies the cos

• governance-auditor

  Use this agent when conducting a deep governance investigation — semantic drift analysis, governance debt inventory, constraint falsifiability scoring, three-frame alignment checks, or governance health reporting. Examples: <example> Context: User runs /governance-audit user: "/governance-audit" ass

• harness-auditor

  Use this agent when verifying the health of the harness itself — checking whether declared enforcement in HARNESS.md matches what actually exists in the project. Examples: <example> Context: User runs /harness-audit user: "/harness-audit" assistant: "I'll use the harness-auditor to check whether the

• harness-discoverer

  Use this agent when scanning a project to discover its tech stack, existing linters, CI configuration, test frameworks, and pre-commit hooks. Examples: <example> Context: User is running /harness-init on a new project user: "/harness-init" assistant: "I'll use the harness-discoverer agent to scan th

• harness-enforcer

  Use this agent when verifying constraints from HARNESS.md against code — running deterministic tools or performing agent-based reviews. Examples: <example> Context: CI needs to check PR constraints user: "Run the harness constraint checks on this PR" assistant: "I'll use the harness-enforcer agent t

• harness-gc

  Use this agent when running garbage collection checks from HARNESS.md — periodic entropy-fighting sweeps for documentation staleness, dead code, convention drift, and dependency currency. Examples: <example> Context: Weekly scheduled garbage collection run user: "Run the weekly garbage collection ch

• integration-agent

  Use when implementation and code review are complete — updates CHANGELOG, commits all changes, opens a PR, watches CI, merges when green, closes the linked issue, and prunes the local branch

• mast

  Use on demand via /mast to read the pact a human authored for themselves — reports each budget key with an observed/inferred/asked flag, refuses to estimate spend it cannot see, notes when a budget was tuned today, and recites the pact's own words rather than only measuring against them; read-only b

• orchestrator

  Use when starting any new feature, fix, improvement, or refactoring task — receives a plain-English task description and coordinates the full pipeline from spec update through to merged PR and closed issue

• reservoir-warden

  Use on demand via /reservoir to watch the human verifier the harness cannot verify — counts observable proxies (session span, decision volume, context switches, wall-clock hour) over the recent git window, reports each with an observed/inferred/asked flag, and if a threshold is crossed offers the si

• spec-writer

  Use when a feature, behaviour change, or improvement needs to be captured in a spec before implementation begins — updates spec and plan files so the project's spec-first discipline is upheld

• tdd-agent

  Use after spec-writer has updated the spec and plan, and the user has approved the plan — writes failing tests that express the new acceptance scenarios, then confirms they are red before any implementation is written

• wip-warden

  Use on demand via /wip to count live sessions against the limit the human declared for themselves — reports the count with its honesty flag, lists which sessions and how long since each last took a turn, and never invents a limit or speculates about the person; counts sessions and never watches the

Hooks (17)

• PreToolUse

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/markdownlint-check.sh

• PostToolUse

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/affordance-invocation-recorder.sh

• PostToolUse

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/commit-constraint-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/drift-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/snapshot-staleness-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/reflection-prompt.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/framework-change-prompt.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/secrets-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/gc-rotate.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/curation-nudge.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/governance-drift-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/mast-boundary-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/reservoir-check.sh

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/session-registry-sweep.sh

• SessionStart

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/session-registry-start.sh

• SessionStart

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/parked-resume-check.sh

• SessionStart

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/wip-check.sh

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