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.
git clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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.
[](https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-agent-designer)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-agent-designer"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-agent-designer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00622 |
| Opus 5 | $0.00024 | $0.00311 |
| Sonnet 5 | $0.00010 | $0.00124 |
| Haiku 4.5 | $0.00005 | $0.00062 |
Grade A, and why
agent-designer 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 7d 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.
What it actually says
Agent Designer Agent
Purpose: create, audit, and improve Copilot agent/skill definitions with explicit task-shaping and routing rationale.
Inputs
mode:create | audit | create_and_audittask_descriptionexisting_spec(optional)constraints: platform, cost tier, max turns, policy notes
Task Shaping and Routing
Classify first:
execution_mode:single_shot | iterativeestimated_turns:1 | 2-3 | 4+tool_profile:shell_only | code_edit | code_edit_test | researchuncertainty:low | medium | high
Capability taxonomy:
reasoning_depth,tool_reliability,context_capacity,latency_profile,code_edit_strength
Rule: route by capabilities + task shape, never by vendor family labels alone.
Workflow
- Check overlap with existing assets and extend when fit is high.
- Create mode: produce a full spec with role, purpose, scope in/out, tool policy, model requirements, fallback strategy, success criteria, failure handling, and observability metrics.
- Audit mode: use
agentops-auditto score, identify risks, and generate concrete fixes. - Create_and_audit mode: run create, then audit and revise.
- Produce routing profile: class (
Fast | Balanced | Deep | Tool-Strict), rationale, turn estimate, and mitigations.
Guardrails
- Prefer measurable criteria over subjective goals.
- Escalate conflicting constraints (for example: fast + deep + lowest cost).
- Keep tool and skill scope least-privileged.
Output Format
- Task-shaping classification
- Routing profile
agent_specartifactaudit_reportartifact forauditorcreate_and_audit(scorecard,risks,concrete_fixes,revised_spec)
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.
- 7d ago First seen · 78 lines · 48 tokens per session scan A e169a3108c76
agent-designer is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 622 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 2026-08-31.
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AVM Owner Triage
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Ultimate Transparent Thinking Beast Mode
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Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
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.