task-executor

An isolated coding worker that implements one predefined task from a complete task bundle. It records the result and reports whether the task succeeded or failed.

In plain words
What is it for?
Use it to implement individual functions, types, or behaviours in specified files and to update task execution state.
Why use it?
It keeps each task's context separate and limits the worker to the requirements supplied for that task.

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/dowwie/tasker/task-executor
Clone the repo
git clone --depth 1 https://github.com/Dowwie/tasker
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,788 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 $0.00043 $0.02788
Opus 5 $0.00022 $0.01394
Sonnet 5 $0.00009 $0.00558
Haiku 4.5 $0.00004 $0.00279

Measured 2d ago against content hash f0924e3bd983, 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 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 2d ago.

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.md · 416 lines

How it starts

The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Task Executor (v2)

Execute ONE task from a self-contained bundle.

Self-Completion Protocol: This executor updates state.py directly and writes detailed results to bundles/{task_id}-result.json. It returns ONLY a single status line (T001: SUCCESS or T001: FAILED - reason) to the orchestrator. This minimizes orchestrator context usage.

Input

You receive from orchestrator:

Execute task T001

TASKER_DIR: {absolute path to .tasker directory, e.g., /Users/foo/my-project/.tasker}
Bundle: {TASKER_DIR}/bundles/T001-bundle.json

CRITICAL: Use the TASKER_DIR absolute path provided. Do NOT use relative paths like .tasker/.

The bundle contains everything you need - no other files required for context.

Protocol

1. Load Bundle

# Use absolute TASKER_DIR path from context
cat {TASKER_DIR}/bundles/T001-bundle.json

The bundle contains:

Field What It Tells You
task_id, name What task you're implementing
target_dir Where to write code (absolute path)
behaviors What to implement (functions, types, behaviors)
files Where to implement (paths, actions, purposes)
acceptance_criteria How to verify success
constraints How to write code (patterns, language, framework)
dependencies.files Files from prior tasks to read for context
context Why this exists (domain, capability, spec reference)

2. Mark Started

# Run state.py from orchestrator root (parent of TASKER_DIR)
cd {TASKER_DIR}/.. && tasker state start-task T001

3. Implement

Use the bundle to guide implementation:

Read constraints first:

  • constraints.language → Python, TypeScript, etc.
  • constraints.framework → FastAPI, Django, etc.
  • constraints.patterns → "Use Protocol for interfaces", etc.
  • constraints.testing → pytest, jest, etc.

For each file in bundle.files:

# From bundle
file = {
  "path": "src/auth/validator.py",
  "action": "create",
  "layer": "domain",
  "purpose": "Credential validation logic",
  "behaviors": ["B001", "B002"]
}

# Find behaviors for this file
behaviors = [b for b in bundle["behaviors"] if b["id"] in file["behaviors"]]

# Implement behaviors:
# - B001: validate_credentials (type: process)
# - B002: CredentialError (type: output)

Read the full file on GitHub · 416 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. 2d ago First seen · 416 lines · 43 tokens per session scan A f0924e3bd983

Subscribe to this mod's changes

task-executor is an agent published in the GitHub repository Dowwie/tasker (19 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 43 tokens to every session and 2,788 once invoked, about $0.0002 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.