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Autonomous Agents Agentic Workflow

SD: Improve Skill Coverage — Autonomous Agents Agentic Workflow

Grow a pack's coverage — improve existing modules, discover new ones, or align them with recent code changes

Available free v1.2.0 Browser
$ sidebutton install agents
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The Skill Discovery agent runs this chain to grow a pack's knowledge coverage over time. It operates in one of three modes, set by the target param:

  • improve (default) — scan the installed modules, pick the one with the weakest knowledge file (lowest confidence, outdated last-verified date, or known gaps), explore that area of the product in a live browser, and raise its coverage.
  • discover — explore the target app for pages and flows not yet covered by a module and scaffold new _skill.md (and _roles/qa.md / se.md once they reach the thresholds) for them.
  • align — for each target repository, find the commits made since the pack was last updated and revise the affected modules so they match the current code: changed selectors and flows, new or removed pages, data-model changes.

The output is a PR on the skill-packs repo that raises confidence, fills gaps, and updates verification timestamps. Dispatch it on a schedule — typically once a day — to keep long-lived packs accurate without manual curation, or on demand from the workspace Run once control with a chosen mode, repo scope, and hint.

Steps

  1. 1.
    Open a terminal
    title
    Agent: SD Coverage
    cwd
    {{entry_path}}
    terminal.open
  2. 2.
    Run a terminal command
    cmd
    |
    terminal.run

Workflow definition

schema_version: 1
id: agent_sd_coverage
title: "SD: Improve Skill Coverage"
description: "Grow a pack's coverage — improve existing modules, discover new ones, or align them with recent code changes"
overview: |
  The Skill Discovery agent runs this chain to grow a pack's knowledge coverage over time. It operates in one of three modes, set by the `target` param:

  - **improve** (default) — scan the installed modules, pick the one with the weakest knowledge file (lowest confidence, outdated last-verified date, or known gaps), explore that area of the product in a live browser, and raise its coverage.
  - **discover** — explore the target app for pages and flows not yet covered by a module and scaffold new `_skill.md` (and `_roles/qa.md` / `se.md` once they reach the thresholds) for them.
  - **align** — for each target repository, find the commits made since the pack was last updated and revise the affected modules so they match the current code: changed selectors and flows, new or removed pages, data-model changes.

  The output is a PR on the skill-packs repo that raises confidence, fills gaps, and updates verification timestamps. Dispatch it on a schedule — typically once a day — to keep long-lived packs accurate without manual curation, or on demand from the workspace Run once control with a chosen mode, repo scope, and hint.

category:
  level: pipeline
  domain: engineering

metadata:
  agent: true
  role: sd

params:
  target:
    type: string
    default: "improve"
    description: "Run mode: improve | discover | align"
  repos:
    type: string
    default: ""
    description: "Target repositories to scope this run to (empty = every repo cloned in the workspace)"
  hint:
    type: string
    default: ""
    description: "Optional extra instructions for the agent"
  entry_path:
    type: string
    default: "~/workspace"
    description: "Working directory for the agent"

steps:
  - type: terminal.open
    title: "Agent: SD Coverage"
    cwd: "{{entry_path}}"
  - type: terminal.run
    cmd: |
      source ~/.agent-env && claude --dangerously-skip-permissions "$(cat <<'SB_PROMPT'
      Learn about the target app and the Skill Discovery methodology (load the sd role playbook and the SD Frontmatter Contract).
      Scope this run to these target repositories: {{repos}}. If that is empty, use every repo cloned in the workspace.

      Operate in '{{target}}' mode:
      - improve: review the skill pack coverage summary, pick the module with the lowest coverage or quality, navigate to it on the target app, snapshot all states and interactions, and raise its coverage.
      - discover: explore the target app for pages, flows, and modules NOT yet covered by a module; scaffold a new _skill.md (and _roles/qa.md / se.md where it reaches the thresholds) for each, following the discovery methodology.
      - align: for each target repository, find the commits made AFTER the pack was last updated (inspect the pack repo git history), then update the affected modules so they match the current code — changed selectors and flows, new or removed pages, and data-model changes.

      In every mode, keep each module's portal-linking frontmatter current — the workspaces:/repos: fields per the SD Frontmatter Contract. Install changes with sidebutton registry update, then commit, push, and create a PR to the skill-packs repo.
      {{hint}}
      Report which modules were created or improved and what was added.
      SB_PROMPT
      )"