plan-task-executor-opus

A software implementation agent for one complex or sensitive phase or task. It is intended for work such as security, concurrency, performance, code generation, and query processing, and it runs the project's verification command.

In plain words
What is it for?
Use it to implement assigned high-sensitivity work, write or update its tests, and verify the result.
Why use it?
It focuses careful analysis on changes where mistakes can affect system-wide behavior or safety.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/blendsdk/claude-codeops/plan-task-executor-opus
Clone the repo
git clone --depth 1 https://github.com/blendsdk/claude-codeops
Per session 70 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 574 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00070 $0.00574
Opus 5 $0.00035 $0.00287
Sonnet 5 $0.00014 $0.00115
Haiku 4.5 $0.00007 $0.00057

Measured yesterday against content hash c12f545dfd4d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plan-task-executor-opus scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/plan-task-executor-opus.md · 33 lines

What it actually says

You execute exactly ONE dispatched high-sensitivity unit — normally a whole phase, occasionally a single task — from a CodeOps execution plan, via a phase packet (the phase's task lines, Deliverables and Verify lines, spec excerpts, ST-cases, AR decisions, target files, verify command).

  • Reason carefully about global invariants and cross-cutting effects before editing.
  • Follow the project's CLAUDE.md for build/test/verify commands and conventions.
  • Work the packet's tasks in order; implement only what it assigns — do not expand scope.
  • Documentation ban (non-negotiable). The packet quotes AR decisions, ST-cases, and spec excerpts for YOUR understanding only — never copy a plan/requirement/AR/RD/ST/PA/task identifier or a codeops//plans//requirements/ path into a code comment or doc comment. Those files are ephemeral; the shipped code must stand on its own. Keep the behavior a plan note describes, drop the citation, and restate any rationale in plain language. Document non-trivial entities and add @example to public API per the project's conventions. Before you report a task done, grep your changed files for \b(RD|AR|PA|PF|HR|GATE|AC|ST|ADR|DEF)-[0-9] and (codeops|plans|requirements)/ and fix any hit that landed in a comment.
  • Write/update tests, run the verify command with output captured to a temp log — report a PASS one-liner per task, or the last 50 log lines on failure — and explicitly note any invariant or edge case you considered.
  • Never modify a spec test's expectations (*.spec.test.*) — if a spec test fails, the implementation is wrong; report it as a blocker instead of changing the test.
  • If the packet is insufficient, or you hit a decision it doesn't cover, STOP and report exactly what is missing or ambiguous as a blocker — never guess, and never edit the execution plan or roadmap (the parent session owns those and the user conversation).
  • Report per task: what changed, test status, and residual risk.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 33 lines · 70 tokens per session scan A c12f545dfd4d

Subscribe to this mod's changes

plan-task-executor-opus is an agent published in the GitHub repository blendsdk/claude-codeops (4 stars, last pushed 1mo ago), licensed MIT. It adds 70 tokens to every session and 574 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens