your-agent-name

A blank template for describing a custom AI agent, including its purpose, abilities, tools, workflows, and examples. The supplied text is placeholder content rather than a description of a finished agent.

In plain words
What is it for?
Use it as a starting point when defining an agent’s instructions, supported tools, use cases, and usage examples.
Why use it?
It provides a structure for documenting an agent, but the input does not identify what a completed agent would actually do.

Agent

Part of the agent-almanac plugin — 58 agents shipped together

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/pjt222/agent-almanac/_template
Clone the repo
git clone --depth 1 https://github.com/pjt222/agent-almanac

Or install agent-almanac, the plugin that ships this one along with the rest of its 58 agents.

Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 723 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 $0.00017 $0.00723
Opus 5 $0.00009 $0.00362
Sonnet 5 $0.00003 $0.00145
Haiku 4.5 $0.00002 $0.00072

Measured 3d ago against content hash e027d8a2e39d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

your-agent-name 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.

agents/_template.md · 109 lines

How it starts

The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Your Agent Name

A comprehensive description of what this agent does and its primary use cases.

Purpose

Explain the specific problem this agent solves or the workflow it enhances.

Capabilities

  • Primary Capability: What the agent does best
  • Secondary Capabilities: Additional features and functionalities
  • Tool Integration: How it leverages available tools
  • MCP Integration: Any MCP server integrations (if applicable)

Available Skills

List the skills from the skills library this agent can execute. Use bare skill IDs (the slash-command names). Group by domain if the agent spans multiple domains, or use a flat list for a small number of skills.

Usage Scenarios

Scenario 1: Primary Use Case

Brief description of the main scenario where this agent excels.

Example command or interaction pattern

Scenario 2: Alternative Use Case

Description of another common use case.

Example command or interaction pattern

Best Practices

  • Guideline 1: How to get the best results
  • Guideline 2: Common pitfalls to avoid
  • Guideline 3: When to use this agent vs others

Examples

Example 1: Basic Usage

User: [Example user request]
Agent: [Expected agent response/behavior]

Example 2: Advanced Usage

User: [Complex user request]
Agent: [Expected agent response/behavior]

Configuration Options (Optional)

Document any configurable parameters, environment variables, or settings that affect this agent's behavior.

Option Default Description
option_name default_value What this option controls

Tool Requirements (Optional)

If this agent requires specific tools beyond the standard set, document them here. Include any MCP server dependencies, external CLIs, or API keys needed.

Limitations

  • Known limitation 1
  • Known limitation 2
  • Situations where this agent might not be appropriate

Read the full file on GitHub · 109 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 · 109 lines · 17 tokens per session scan A e027d8a2e39d

Subscribe to this mod's changes

your-agent-name is an agent published in the GitHub repository pjt222/agent-almanac (31 stars, last pushed 6d ago), licensed MIT. It adds 17 tokens to every session and 723 once invoked, about $0.0001 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.

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