⚠️ CRITICAL INSTRUCTION — READ THIS FIRST, BEFORE CALLING ANY TOOLS ⚠️

DO NOT call adk-session-get, agent-run-messages, memory-search, or any other tool to look up the session.
The COMPLETE transcript is already embedded in this prompt under "## Transcript" below.
Your ONLY tool calls in this task are workspace_bash to run the two flow CLI commands at the bottom.

---

You are auditing an OpenCode agent session for process quality — how well the agent used the flow CLI and tooling, NOT what was built.

The complete session transcript is embedded below in the "## Transcript" section. Read it directly from this prompt — it is already here. Do NOT call any tools to fetch sessions, runs, or messages.

Session metadata

Title: implement/sc-taskify-complete-task
Job: implement
Scenario: sc-taskify-complete-task
Messages: 17
Status: stop

Transcript

[USER]
Implement scenario sc-taskify-complete-task. Your working directory is /workspace. Branch implement/sc-taskify-complete-task is already checked out. GITHUB_TOKEN, FLOW_TOKEN, FLOW_SERVER_URL, FLOW_GITHUB_OWNER, FLOW_GITHUB_REPO, FLOW_PLAN_BRANCH_NAME are injected as env vars. Use workspace tools to implement. Use flow git-proxy git push and flow git-proxy gh pr create for git operations — auth is handled automatically. Do NOT call trigger_agent, spawn_agents, or list_available_agents. Push with flow git-proxy git push --force-with-lease origin implement/sc-taskify-complete-task and open a PR with flow git-proxy gh pr create --title "implement: sc-taskify-complete-task" --body "Implements sc-taskify-complete-task" --base main --head implement/sc-taskify-complete-task (exit 0 whether new or already exists).

Session context (do not rediscover — use these values directly)

• Scenario key: sc-taskify-complete-task
• Implement branch: implement/sc-taskify-complete-task (already checked out — do NOT run git checkout)
• Plan branch: plan/main (FLOW_PLAN_BRANCH_NAME is already set in env)
• GitHub repo: https://github.com/emergent-company/taskify-api
• FLOW_TOKEN: flt_0fa3f97d166559bd9160cc4aa95160842441c5b1

Scenario graph: sc-taskify-complete-task

[Scenario] sc-taskify-complete-task
-[has]-> [ScenarioStep] step-taskify-complete-task-request "Client sends PATCH /tasks/{id}/complete and receives the updated task with compl..." [not_existing]
-[acted_by]-> [Actor] actor-user "User" [not_existing]
-[belongs_to]-> [Domain] domain-task "Task" [not_existing]
-[occurs_in]-> [Context] ctx-taskify-complete-task "PATCH /tasks/{id}/complete endpoint"
-[requires]-> [APIEndpoint] ep-taskify-complete-task (file=handler/tasks.go, handler=HandleCompleteTask, method=PATCH, path=/tasks/{id}/complete)
-[calls]-> [ServiceMethod] svc-taskify-complete "CompleteTask" (file=service/tasks.go)
-[uses]-> [SQLQuery] sq-complete-task "CompleteTask" (file=db/queries/tasks.sql)

Follow these instructions:

Memory sandbox implementation rules

Environment

Branch already checked out at /workspace. Tools: workspace_bash, workspace_read, workspace_write, workspace_edit, workspace_glob, workspace_grep, workspace_git.

FLOW_TOKEN and FLOW_SERVER_URL are env vars. Use flow git-proxy for all git/gh operations — it handles GitHub App auth automatically. Do NOT use git remote set-url, do NOT use raw GITHUB_TOKEN.

CRITICAL: Do NOT call agent tools

Do NOT call list_available_agents, spawn_agents, trigger_agent, search-knowledge, skill, or skill-get.

Steps

1. Read scenario from pre-injected graph in prompt.
2. Write code files with workspace_write/workspace_edit.
3. Commit: git add -A && git commit -m "implement: <key>"
4. Push: flow git-proxy git push --force-with-lease origin <branch>
5. PR: flow git-proxy gh pr create --title "implement: <key>" --body "Implements <key>" --base main --head <branch> — exit 0 whether new or already exists.
6. Stop.

Follow these instructions:

---

name: caveman
description: >
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman
while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra,
wenyan-lite, wenyan-full, wenyan-ultra.
Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens",
"be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

Respond terse like smart caveman. All technical substance stay. Only fluff die.

Persistence

ACTIVE EVERY RESPONSE. No revert after many turns. No filler drift. Still active if unsure. Off only: "stop caveman" / "normal mode".

Default: full. Switch: /caveman lite|full|ultra.

Rules

Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging. Fragments OK. Short synonyms (big not extensive, fix not "implement a solution for"). Technical terms exact. Code blocks unchanged. Errors quoted exact.

Pattern: [thing] [action] [reason]. [next step].

Not: "Sure! I'd be happy to help you with that. The issue you're experiencing is likely caused by..."
Yes: "Bug in auth middleware. Token expiry check use < not <=. Fix:"

Intensity

Level	What change
lite	No filler/hedging. Keep articles + full sentences. Professional but tight
full	Drop articles, fragments OK, short synonyms. Classic caveman
ultra	Abbreviate (DB/auth/config/req/res/fn/impl), strip conjunctions, arrows for causality (X → Y), one word when one word enough
wenyan-lite	Semi-classical. Drop filler/hedging but keep grammar structure, classical register
wenyan-full	Maximum classical terseness. Fully 文言文. 80-90% character reduction. Classical sentence patterns, verbs precede objects, subjects often omitted, classical particles (之/乃/為/其)
wenyan-ultra	Extreme abbreviation while keeping classical Chinese feel. Maximum compression, ultra terse

Example — "Why React component re-render?"

• lite: "Your component re-renders because you create a new object reference each render. Wrap it in useMemo."
• full: "New object ref each render. Inline object prop = new ref = re-render. Wrap in useMemo."
• ultra: "Inline obj prop → new ref → re-render. useMemo."

Auto-Clarity

Drop caveman for: security warnings, irreversible action confirmations, multi-step sequences where fragment order risks misread, user asks to clarify or repeats question. Resume caveman after clear part done.

Boundaries

Code/commits/PRs: write normal. "stop caveman" or "normal mode": revert. Level persist until changed or session end.

[ASSISTANT]
Code implemented. Git push failed via proxy due to token error. PR creation failed due to token error. Manual intervention required for auth. Stop.

Your task

Read the transcript above carefully, then focus ONLY on process quality (not implementation details):

1. Did the agent use flow CLI commands correctly? Note any misuse, wrong flags, or commands run in the wrong order.
2. Were there crashes, errors, or retries? How many times did the agent repeat the same command?
3. Did the agent follow the skill instructions (load skill → read graph → implement → verify)? Where did it deviate?
4. Was the session efficient? Flag any unnecessary loops, redundant reads, or wasted turns.
5. Rate process quality: excellent / good / needs-improvement / poor

Step 1 — Set credentials and write your findings back using the flow CLI:

Use workspace_bash with the field name "command" (not "bash_command"). Run these three lines as a single command string:

export FLOW_TOKEN=flt_0fa3f97d166559bd9160cc4aa95160842441c5b1
export FLOW_SERVER_URL=https://flow-dev.emergent-company.ai
flow report analyze as-efa9fb6f --notes "<2-3 sentence process summary>" --findings "||" --type process --analyst auto

The command will print the asa key (e.g. "Analysis recorded: asa-XXXXXXXX-N"). Use that key in Step 2.

Step 2 — Record structured feedback items using the asa key from Step 1:

flow report feedback --items "||..."

Each item format: target:category:severity:summary

Valid targets:
flow-cli — the flow CLI tool itself (bugs, missing flags, wrong behavior)
skill: — a specific skill file (e.g. skill:flow-implement-scenario)
opencode — the OpenCode platform (session handling, API behavior)
prompt-design — how prompts/instructions are written
process-design — the overall workflow/process design

Valid categories:
crash — tool or command crashed / errored unexpectedly
misuse — agent used a command incorrectly
inefficiency — unnecessary repetition or wasted turns
retry-loop — agent retried the same failing command without changing approach
wrong-order — steps executed in wrong sequence
missing-guidance — skill or prompt lacked instruction the agent needed

Valid severities: high | medium | low

Only create feedback items for real, specific problems you observed in the transcript. Skip Step 2 if the session had no process issues.