agent-profiles

agent-profiles is a skill for Claude Code, Codex from humanerd-drew/opencode-drewgent. It costs 62 tokens per session (1,690 once invoked), scanned A, original, MIT.

A set of predefined roles for subagents, where each role specifies the model, service provider, tools, and instructions used for a task.

In plain words
What is it for?
Use it to define specialist subagents, choose models by cost or capability, build task pipelines, and route work that needs escalation.
Why use it?
It avoids repeating the same setup whenever you delegate work to another agent and makes role assignments consistent.

Skill for Claude CodeCodex

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 skills/humanerd-drew/opencode-drewgent/agent-profiles
Any agent
npx skills add humanerd-drew/opencode-drewgent --skill agent-profiles
Clone the repo
git clone --depth 1 https://github.com/humanerd-drew/opencode-drewgent

Made for: Claude Code, Codex.

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,690 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 $0.00062 $0.01690
Opus 5 $0.00031 $0.00845
Sonnet 5 $0.00012 $0.00338
Haiku 4.5 $0.00006 $0.00169

Measured 3d ago against content hash 633fd1cab3bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-profiles 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 3d 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.

skills/agent-profiles/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Profiles

Agent profiles are pre-defined subagent roles loaded by task(subagent_type="<name>", description="summary", prompt="..."). Each profile sets model, provider, toolsets, and system instructions in one call.

Location

Profiles live at $HERMES_HOME/agents/*.md. For {{AGENT_NAME}}: ~/.{{AGENT_NAME_LOWER}}/agents/.

Format

Each profile is a Markdown file with YAML frontmatter and markdown body:

---
name: profile-name
description: >
  Brief description of this profile's purpose.
model: deepseek-v4-flash
provider: opencode-go
toolsets: [terminal, file, search]
created: YYYY-MM-DD
---

# Profile Name

You are a [role definition]. Your job is to...

## Rules

- Specific constraints (read-only, write-only, review-only, etc.)

## Escalation

When creating new autonomous capabilities, **prefer assigning a single agent profile over building a multi-stage pipeline.**

| Approach | When | Why |
|----------|------|-----|
| **Profile-first** | Agent acts autonomously (observe → decide → act) | Simpler, faster to iterate, one agent owns the full cycle |
| **Pipeline-first** | Multi-stage processing with distinct roles | Necessary when stages need different models/tools or parallel execution |

**Origin:** The CMO agent (content-manager) started as a 5-stage pipeline design. The user corrected it: "워크플로우 만들어두고 에이전트 배정하고 기록 뒤져서 바로 만들어볼 수 있지 않겠니." The simpler approach won — one agent profile + cron scheduling + one narrative tracking file. Pipelines add accidental complexity. Start with a profile; split into stages only when there's a clear reason.

## The 8 Standard Profiles

### Flash Tier ($0 marginal cost — OpenCode Go subscription)

| Profile | Model | Role | ESCALATE? |
|---------|-------|------|-----------|
| **explorer** | deepseek-v4-flash | Read-only codebase analysis, context gathering | ✅ |
| **implementer** | deepseek-v4-flash | Code implementation, file creation | ✅ |
| **tester** | deepseek-v4-flash | Test writing + verification | ✅ |
| **archiver** | deepseek-v4-flash | Documentation, changelog, completion summary | ❌ |

### Pro/Max Tier (stronger models, selective use)\n\n| Profile | Model | Role |\n|---------|-------|------|\n| **content-manager** | deepseek-v4-pro | CMO agent — observes work, produces multi-format content (blog + SVG cover + X thread + Excalidraw PNG), tracks narrative arc. Runs daily via cron, delivers to Discord. |\n| **reviewer** | deepseek-v4-pro | General code review (logic, style, edge cases) |\n| **reviewer-critical** | qwen3.7-max | In-depth review for large/architectural changes |\n| **security-reviewer** | qwen3.7-max | Security audit (auth, crypto, injection, secrets) |\n| **planner** | qwen3.7-max | Task decomposition, tier assignment, pipeline design |

## Pipeline Pattern

Sequential multi-stage workflows use individual `task()` calls:

```python
task(
    subagent_type="explorer",
    description="Analyze auth code",
    prompt="analyze the existing auth code"
)
task(
    subagent_type="implementer",
    description="Implement login validation",
    prompt="implement login validation"
)
task(
    subagent_type="tester",
    description="Write tests",
    prompt="write tests for login"
)
task(
    subagent_type="reviewer",
    description="Review auth changes",
    prompt="review the auth changes"
)

Or via kanban pipeline automation:

kanban_create(
    title="Add login validation",
    pipeline=["explorer", "implementer", "tester", "reviewer", "archiver"],
    body="...",
)

Tiered Pipeline by Complexity

Tier 1 (trivial): Implementer(flash) → Archiver(flash) — typo fix, rename Tier 2 (moderate): Explorer(flash) → Implementer(flash) ↔ Tester(flash) [≤2 loops] → Archiver(flash) Tier 3 (complex): Planner(max) → Explorer(flash) → Implementer(flash) ↔ Tester(flash) [≤3 loops] → Reviewer(pro) → [security?] → Security-reviewer(max) → [critical?] → Reviewer-critical(max) → Archiver(flash)

Design Principles

1. Never assume provider topology. The user may route through any provider (OpenCode Go, OpenRouter, MiniMax direct, etc.). Always verify the actual config before designing routing strategy.

Read the full file on GitHub · 150 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. 3d ago First seen · 150 lines · 0 tokens per session scan A 633fd1cab3bf

Subscribe to this mod's changes

agent-profiles is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (2 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 1,690 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.