goal-overseer

goal-overseer is an agent for Claude Code from Zeekeey-jpeg/LeRoy-HQ. It costs 62 tokens per session (1,741 once invoked), scanned A, original, MIT.

An autonomous agent that coordinates the steps of a high-effort goal by assigning work to specialist agents and recording checkpoints.

In plain words
What is it for?
Use it for high-effort goals that need step-by-step execution, specialist delegation, progress checkpoints, failure alerts, and a final completion notice.
Why use it?
It helps long-running goals continue through multiple steps and recover from failures without losing completed progress.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Good fit Use it for high-effort goals that need step-by-step execution, specialist delegation, progress checkpoints, failure alerts, and a final completion notice.

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Install with agentmods
npx agentmods add agents/zeekeey-jpeg/leroy-hq/goal-overseer
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.

Clone the repo
git clone --depth 1 https://github.com/Zeekeey-jpeg/LeRoy-HQ

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for goal-overseer

README.md
[![agentmods](https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/goal-overseer/github.svg)](https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/goal-overseer)
Your own site
<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/goal-overseer"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/goal-overseer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for goal-overseer

Your own site · 80×15
<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/goal-overseer"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/goal-overseer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,741 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00062 $0.01741
Opus 5 $0.00031 $0.00870
Sonnet 5 $0.00012 $0.00348
Haiku 4.5 $0.00006 $0.00174

Measured 12d ago against content hash d300707348e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

goal-overseer 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 12d 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.

core/agents/goal-overseer.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.

Goal Overseer Agent

Autonomous orchestrator for High Effort goals. Spawned once per High Effort goal. Runs to completion or pauses on failure. Checkpoint-per-step ensures no work is lost on resume.

Notifications: This agent sends alerts and completion pings over a notification channel (e.g. an optional messaging connector configured via leroy mcp add). If no channel is configured, notifications fail silently and execution continues.


Spawn Conditions

  • Always spawned by COO when a High Effort goal is created or resumed
  • NEVER spawned for Standard goals
  • NEVER spawned manually — only via goal-engine.md skill
  • One overseer per goal at a time (dedup via overseer_task_id in goals.json)

On Spawn — Read These First

  1. scripts/goal_manager.py — all state mutations (public API only, never edit goals.json directly)
  2. session/goals.json — current goal state
  3. agents/goal-overseer.md (this file) — execution protocol

Identify the goal by goal_id from the spawn prompt. Confirm status = running before proceeding.


Core Execution Loop

for step_idx from resume_from to len(actions) - 1:
    action = actions[step_idx]
    
    1. Log: "Starting step {step_idx + 1}/{total}: {action}"
    2. Infer specialist type from action text (see table below)
    3. Spawn specialist agent via TaskCreate (foreground — wait for result)
    4. Evaluate result quality
       - Success → set_checkpoint(goal_id, step_idx) → advance_step(goal_id) → continue
       - Failure → pause_goal(goal_id, step_idx, error) → send alert → EXIT

On all steps complete:
    5. mark_done(goal_id)
    6. send completion ping
    7. set_notified(goal_id)

Specialist Selection Table

Infer from action text keywords:

Keywords in action text Specialist
research, analyze, investigate, find, survey, audit scout
web, scrape, fetch, search the internet scraper (with WebSearch tool)
implement, write, build, code, create, refactor, fix builder
test, validate, verify, check quality, run tests guardian
notify, message, send an alert COO executes directly via the notification channel
deploy, push, release, commit builder + guardian review
design, layout, UI, component designer
database, query, schema builder with the relevant data connector
CRM / ticketing / external system builder with the relevant connector
default (no match) builder

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. 12d ago First seen · 246 lines · 62 tokens per session scan A d300707348e1

Subscribe to this mod's changes

goal-overseer is an agent published in the GitHub repository Zeekeey-jpeg/LeRoy-HQ (10 stars, last pushed 19d ago), licensed MIT. It adds 62 tokens to every session and 1,741 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.

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