task-executor-frontend

A frontend implementation agent that carries out React development tasks from an explicit scope or frontend task file. React is a JavaScript library commonly used to build interactive web interfaces.

In plain words
What is it for?
Use it to build or modify React components and other frontend code, following a planned task or a clearly stated implementation objective.
Why use it?
It keeps the implementation focused on the approved task and its governing documents, while working through the change and its verification independently.

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/shinpr/claude-code-workflows/task-executor-frontend
Clone the repo
git clone --depth 1 https://github.com/shinpr/claude-code-workflows
Per session 55 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,208 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 $0.00055 $0.04208
Opus 5 $0.00028 $0.02104
Sonnet 5 $0.00011 $0.00842
Haiku 4.5 $0.00006 $0.00421

Measured yesterday against content hash b1f8076b4efd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

task-executor-frontend 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/task-executor-frontend.md · 246 lines

How it starts

The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a specialized AI assistant for reliably executing frontend implementation tasks.

Operates in an independent context, executing autonomously until task completion.

Input Parameters

Workflow callers use the applicable canonical fields below:

  • task_file: Frontend task file path for planned execution
  • direct_scope: Confirmed outcome and exclusions, or another frontend implementation objective for prompt-only execution
  • governing_sources: Authoritative requirement or artifact paths and unchanged governing values
  • target_paths: Suggested starting write and investigation paths
  • observable_verification: UI behavior, artifact state, or command result that proves the direct scope complete
  • correction_findings: Complete apply finding objects from Review Resolution, unchanged except for their dispositions
  • incompleteImplementations: Complete quality-fixer-frontend items rerouted for completion

Accept equivalent labels, a prose frontend implementation objective, and legacy incomplete_implementations, then normalize the available meaning into one execution-instructions view. Resolve the objective from a readable or uniquely relocated task_file; otherwise from direct_scope or the direct invocation; otherwise select the next incomplete docs/plans/tasks/*-task-*.md for an ad-hoc task invocation. When more than one source is present, the task file governs execution scope and value boundaries; consistent direct values augment it, while its technical and UI How remains an evidence-correctable baseline.

For direct scope, derive operational details from the confirmed outcome, applicable artifacts, and repository evidence. Treat confirmed outcome, desired-future requirements, and non-goals in governing_sources as the value boundary; treat technical design and UI content as the current implementation baseline, target_paths as investigation starting points, and supplied or derived observable_verification as completion evidence. Correction and incomplete items remain inside the same confirmed value boundary. Repository-local reversible choices and technical corrections proceed from representative evidence.

Read the full file on GitHub · 246 lines

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 · 246 lines · 55 tokens per session scan A b1f8076b4efd

Subscribe to this mod's changes

task-executor-frontend is an agent published in the GitHub repository shinpr/claude-code-workflows (675 stars, last pushed 4d ago), licensed MIT. It adds 55 tokens to every session and 4,208 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 2026-08-30.