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mvanderbend-msoft ebd22496dd Add acreadiness-cockpit plugin (AgentRC measure -> generate -> maintain) 🤖🤖🤖 (#1593)
* Add acreadiness-cockpit plugin

Adds a new plugin that drives Microsoft AgentRC from Copilot chat,
framing every interaction inside AgentRC's Measure -> Generate ->
Maintain loop.

Custom agent (agents/ai-readiness-reporter.agent.md):
  Runs `agentrc readiness --json`, interprets every result against
  the 9-pillar / 5-level maturity model, then renders a self-contained
  reports/index.html from a fixed HTML/CSS template (bundled with the
  acreadiness-assess skill) so every user gets an identically styled
  dashboard. Honours policies (disabled criteria, overrides, pass-rate
  thresholds) and surfaces extras separately.

Skills:
  - acreadiness-assess: Measure step. Wraps `agentrc readiness --json`
    and hands off to the @ai-readiness-reporter agent. Bundles the
    canonical report-template.html.
  - acreadiness-generate-instructions: Generate step. Wraps
    `agentrc instructions`. Defaults to .github/copilot-instructions.md
    (Copilot-native). Asks flat vs nested. For monorepos, emits per-area
    .github/instructions/<area>.instructions.md files with applyTo
    globs taken from agentrc.config.json.
  - acreadiness-policy: Maintain step. Helps pick, scaffold, or apply an
    AgentRC policy (criteria.disable, criteria.override, extras,
    thresholds) and wire it into CI via --fail-level.

Plugin (plugins/acreadiness-cockpit/):
  Declarative plugin.json referencing the agent and three skills.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address PR review feedback

- Align documented slash-command names with plugin manifest:
  /acreadiness-assess, /acreadiness-generate-instructions,
  /acreadiness-policy (was /assess, /generate-instructions, /policy
  inside SKILL bodies and argument-hints).
- Move the literal % from the report template into the substituted
  values for {{passRate}} and {{threshold}} so an N/A value of '—'
  no longer renders as '—%'. Updated the agent placeholder contract
  accordingly.
- Point the report footer at the canonical plugin folder under
  github/awesome-copilot instead of the personal source fork.
- Add explicit HTML-escaping rules to the agent: HTML-escape every
  {{placeholder}} substitution, and replace </script with <\/script
  inside the embedded JSON block so untrusted repo content cannot
  break the markup or inject scripts.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-04 14:11:14 +10:00

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name, description, argument-hint
name description argument-hint
acreadiness-assess Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo. [--policy <path-or-pkg>] [--per-area] — e.g. /acreadiness-assess, /acreadiness-assess --policy ./policies/strict.json

/acreadiness-assess — AI-readiness assessment

Use this skill whenever the user asks for an AI-readiness assessment, a readiness check, an audit, or wants to see how AI-ready their repository is.

This skill is the Measure step in AgentRC's Measure → Generate → Maintain loop. The result is a self-contained HTML dashboard the user can open with file:// or commit to the repo.

Steps

  1. Confirm prerequisites. Node 20+ must be on PATH. If unsure, run node --version.

  2. Decide on a policy (optional but encouraged):

    • If the user provided --policy <source>, capture it.
    • Otherwise check agentrc.config.json for a policies array.
    • If neither, run with no policy (built-in defaults).
    • For a primer on policies, suggest the acreadiness-policy skill.
  3. Run the readiness scan in the repo root with structured output:

    npx -y github:microsoft/agentrc readiness --json [--policy <source>] [--per-area]
    

    The CommandResult<T> JSON envelope is your input for the next step.

  4. Hand off to the ai-readiness-reporter custom agent to interpret the JSON and produce reports/index.html. The agent renders via the bundled template report-template.html (shipped alongside this skill) so every report has an identical look & feel. The agent:

    • Reads the bundled report-template.html and substitutes placeholders with real data.
    • Inlines all CSS, ships a single static file (works under file://).
    • Renders maturity level, overall score, grade, pass-rate vs threshold.
    • Breaks down all 9 pillars across Repo Health (8) and AI Setup (1) with what it measures, why it matters for AI, current state, and a specific recommendation.
    • Tags every pillar with an AI relevance badge (High / Medium / Low).
    • Surfaces Extras separately (they never affect the score).
    • Shows the Active Policy including any disabled/overridden criteria and thresholds.
    • Produces a Prioritised Remediation Plan (🔴 Fix First / 🟡 Fix Next / 🔵 Plan).
    • Embeds the raw AgentRC JSON for reuse.
  5. Tell the user where the report lives (reports/index.html) and how to open it. Summarise in chat: maturity level, overall score, top three lowest pillars, and the single highest-leverage next action (almost always: run the acreadiness-generate-instructions skill).

Notes

  • AgentRC also has a built-in HTML renderer (--visual / --output report.html) but its output is intentionally generic. This skill produces a tailored, opinionated dashboard via the custom agent — closer to a code review than a metrics dump.
  • For CI gating, recommend agentrc readiness --fail-level <n> (15).
  • The skill never modifies repository files other than creating reports/index.html.