Thoughtbox

You are implementing the “AgentOps Day‑0 Bootstrap” inside this repository. Your job is to create a minimal but correct end-to-end pipeline that: 1) runs daily on a schedule to generate a Thoughtbox dev digest + 2–3 proposals, 2) opens a GitHub Issue with that content and an embedded machine-readable payload, 3) waits for human approval via label(s), 4) on approval label, runs an implementation/evaluation job (even if initially stubbed), 5) posts an evidence comment back to the issue (and optionally opens a PR), 6) emits durable artifacts + LangSmith trace links for every run. Use the existing workflow style and gates from: `.claude/commands/specifications/specification-suite.md` as the reference pattern for: - phase structure (detect state → design → validate → orchestrate) - state persistence - gates/checklists - artifacts and audit logs You MUST implement this in a way that can be completed today: - prioritize correctness, determinism, and auditability - OK to stub the “LLM intelligence” parts initially, but the workflow chain MUST work end-to-end - keep everything isolated under `agentops/` and `.github/workflows/` unless there’s a clear reason otherwise --- ## Phase 0 — Session detection (like spec-suite) 1) Detect whether `agentops/` already exists and whether there are previous bootstrap artifacts: - if `.agentops-bootstrap/` exists, read `.agentops-bootstrap/state.json` 2) If bootstrap already partially exists: - produce a short “resume plan” and continue without duplicating files. Write progress to: `.agentops-bootstrap/state.json` and produce human-readable logs in: `.agentops-bootstrap/summary.md` Gate: - [ ] You can explain what already exists and what you will change. --- ## Phase 1 — Design (plan the implementation) ### Deliverables you must create (file-level checklist) A) Templates & fixtures - `agentops/templates/daily_thoughtbox_dev_brief_issue.md` - `agentops/templates/implementation_evidence_comment.md` - `agentops/fixtures/run_summary.example.json` - `agentops/fixtures/proposals.example.json` (Use the template/fixtures content provided to you by the human in this chat; do not invent incompatible schemas.) B) Runner (CLI) that can run locally and in CI Implement a small runner in the repo’s most natural language (prefer the repo’s existing stack). It must support two commands: 1) `daily-dev-brief` - produces artifacts: - `artifacts/digest.md` - `artifacts/proposals.json` - `artifacts/issue_body.md` (rendered from the template) - `run_summary.json` - and then posts/opens a GitHub Issue using the rendered body 2) `implement-proposal --proposal-id proposal-1 --issue-number N` - fetches the issue body from GitHub - extracts embedded `proposals.json` - selects the proposal by id - performs an implementation step (can be stubbed Day‑0): - minimal acceptable behavior Day‑0: - create a branch name `agent/{proposal-id}/{run_id}` - write a placeholder patch or create a TODO file under `agentops/runs/...` (do NOT pollute product code) - run the repo tests (or a no-op if none exist) and capture logs - produce `implementation_report.md` and `eval_report.md` (can be stubbed) - posts a comment to the issue using the evidence template - optionally opens a draft PR (if safe and configured) C) GitHub Actions workflows - `.github/workflows/agentops_daily_thoughtbox_dev.yml` - schedule (cron) + workflow_dispatch - runs `daily-dev-brief` - uploads artifacts - `.github/workflows/agentops_on_approval_label.yml` - triggers on issue labeled: `approved:proposal-1|2|3` - runs `implement-proposal` for that proposal - uploads artifacts - comments evidence back to the issue D) Setup / docs - `agentops/SETUP.md` documenting: - required GitHub secrets - required labels to create - how to run locally - how to run in GitHub Actions - governance/safety rules (no external messaging) ### Human input you must request (only what is actually blocking) Before coding anything that depends on these, ask the human for: 1) Where should the workflows run? - GitHub-hosted runners (default) - or self-hosted runner (if we need local tools like Claude Code/Cursor) 2) Secrets availability: - `LANGSMITH_API_KEY` (yes/no; name to use) - at least one model API key if we implement real proposal generation: - `OPENAI_API_KEY` and/or `ANTHROPIC_API_KEY` 3) Should the implementation workflow open PRs automatically? - yes (requires `pull-requests: write`) - no (just attach patch + instructions) 4) Desired daily schedule time in America/Chicago (default: 06:30) If the human doesn’t answer immediately, proceed with safe defaults: - GitHub-hosted runners - no PR auto-open (just comment evidence + attach artifacts) - schedule at 06:30 America/Chicago - proposal generation stubbed unless API keys exist Gate: - [ ] A written design plan exists in `.agentops-bootstrap/summary.md` - [ ] File list and acceptance criteria are explicit --- ## Phase 2 — Validate (like spec-validator) Implement lightweight validation checks: - Validate that `proposals.json` conforms to the canonical schema: - has `run_id` - has `proposals` array length 2–3 - each proposal has `proposal_id`, `title`, `test_plan`, `touch_points`, `rollback` - Validate that issue body includes: - `AGENTOPS_META_BEGIN ... END` - `proposals.json` JSON block parseable - Validate workflows YAML syntax (best-effort) - Validate runner can execute in a clean environment Add a small test script (or unit tests) under `agentops/tests/` that: - loads fixtures - renders the issue body template - parses back the embedded JSON deterministically Gate: - [ ] `agentops/tests` pass locally (or via CI) with fixtures - [ ] The “extract proposals from issue body” logic works --- ## Phase 3 — Orchestrate (implementation) ### Implementation details (constraints) - Keep new dependencies minimal; prefer standard libs. - All runs MUST emit: - `run_summary.json` - `logs.txt` - `artifacts/` folder - For Day‑0, scanning the web and real LLM proposal generation can be stubbed, BUT the runner must be structured so it’s easy to plug in the real logic later. ### LangSmith tracing If `LANGSMITH_API_KEY` is present: - create a trace per run tagged with: - `run_id`, `job_name`, `proposal_id` (if applicable), `git_sha` - record major steps as spans: - ingest/sense, synthesize, render issue, post issue - implement, test, eval, comment evidence If not present: - run without tracing but still include `trace: null` in run_summary. ### GitHub integration Use GitHub API (or `gh` CLI if available) to: - create issue (daily workflow) - fetch issue body (implementation workflow) - post comment back Keep permissions minimal in workflow YAML. ### Labels Ensure the repo has these labels (document in SETUP.md): - `agentops` - `dev-brief` - `approved:proposal-1` - `approved:proposal-2` - `approved:proposal-3` - `hold` - `rejected` (You may add a small script to create labels via API, but don’t block Day‑0 on it.) Gate: - [ ] Running the daily workflow produces an issue with embedded proposals JSON - [ ] Applying `approved:proposal-1` triggers the second workflow and posts an evidence comment - [ ] Artifacts are uploaded for both workflows - [ ] No unsafe actions (no external comms, no prod changes) --- ## Final output requirements At the end, provide: 1) a short “How to run it today” section, 2) a list of all files created/modified, 3) what human needs to set (secrets/labels), 4) known limitations and next steps for plugging in real proposal intelligence.