add-prompt

add-prompt is a skill for Claude Code from cyanheads/evals-mcp-server. It costs 37 tokens per session (1,582 once invoked), scanned A, a copy of add-prompt, Apache-2.0.

A template and workflow for adding reusable MCP prompt definitions to a TypeScript project. MCP, or Model Context Protocol, is a way for an AI client to use tools and prompts supplied by a server.

In plain words
What is it for?
Use it when creating a new reusable message template for an LLM interaction. It guides you to create the prompt file, register it with the server and run the project's development check.
Why use it?
It removes the guesswork from placing, naming and registering a new prompt. It also specifies a project check to catch registration or typing errors.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the evals-mcp-server plugin — 33 skills, 1 MCP server shipped together

Good fit Use it when creating a new reusable message template for an LLM interaction. It guides you to create the prompt file, register it with the server and run the project's development check.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cyanheads/evals-mcp-server/add-prompt
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.

Any agent
npx skills add cyanheads/evals-mcp-server --skill add-prompt
Clone the repo
git clone --depth 1 https://github.com/cyanheads/evals-mcp-server

Made for: Claude Code.

Or install evals-mcp-server, the plugin that ships this one along with the rest of its 33 skills, 1 MCP server.

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 add-prompt

README.md
[![agentmods](https://agentmods.dev/badge/skills/cyanheads/evals-mcp-server/add-prompt/github.svg)](https://agentmods.dev/skills/cyanheads/evals-mcp-server/add-prompt)
Your own site
<a href="https://agentmods.dev/skills/cyanheads/evals-mcp-server/add-prompt"><img src="https://agentmods.dev/badge/skills/cyanheads/evals-mcp-server/add-prompt/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 add-prompt

Your own site · 80×15
<a href="https://agentmods.dev/skills/cyanheads/evals-mcp-server/add-prompt"><img src="https://agentmods.dev/badge/skills/cyanheads/evals-mcp-server/add-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,582 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 100% copy Near-identical to another mod 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 $0.00037 $0.01582
Opus 5.5 $0.00015 $0.00633
Sonnet 5.5 $0.00007 $0.00316
Haiku 4.5 $0.00004 $0.00158

Measured 9d ago against content hash aee181ba52ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

add-prompt 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 9d 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.

Origin

This is a copy

100% identical to add-prompt — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

framework-skills/add-prompt/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context

Prompts use the prompt() builder from @cyanheads/mcp-ts-core. Each prompt lives in src/mcp-server/prompts/definitions/ with a .prompt.ts suffix. The standard registration pattern uses a definitions/index.ts barrel that collects all prompts into an allPromptDefinitions array for createApp(). Fresh scaffolds start with direct imports in src/index.ts — the barrel is introduced as definitions grow. Match the pattern already used by the project you're editing.

Prompts are pure message templates — no Context, no auth, no side effects. generate can be sync or async (returns PromptMessage[] | Promise<PromptMessage[]>).

Steps

  1. Gather the prompt's name, purpose, and arguments from the user's request — ask only if genuinely absent
  2. Create the file at src/mcp-server/prompts/definitions/{{prompt-name}}.prompt.ts
  3. Register the prompt in the project's existing createApp() prompt list (directly in src/index.ts for fresh scaffolds, or via a barrel if the repo already has one)
  4. Run bun run devcheck to verify
  5. Smoke-test with bun run rebuild && bun run start:stdio < /dev/null — the Core services constructed log record must list the new prompt in its prompts field (the message text shows only counts); if it doesn't, the prompt never reached createApp()

Template

/**
 * @fileoverview {{PROMPT_DESCRIPTION}}
 * @module mcp-server/prompts/definitions/{{PROMPT_NAME}}
 */

import { completable, prompt, z } from '@cyanheads/mcp-ts-core';

export const {{PROMPT_EXPORT}} = prompt('{{prompt_name}}', {
  description: '{{PROMPT_DESCRIPTION}}',
  // title is optional — human-readable display name surfaced in prompts/list.
  // title: '{{PROMPT_DISPLAY_TITLE}}',
  // args is optional — omit entirely for prompts with no parameters.
  // When present, all fields need .describe(). Only JSON-Schema-serializable types allowed.
  // Wrap any field with completable() to enable argument autocompletion.
  args: z.object({
    // All fields need .describe()
    // language: completable(z.string().describe('Language'), async (partial) => matchingLanguages(partial)),
  }),
  generate: (args) => [
    {
      role: 'user',
      content: {
        type: 'text',
        text: `{{PROMPT_TEMPLATE_TEXT}}`,
      },
    },
  ],
});

Read the full file on GitHub · 144 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. 9d ago Changed · +6 lines aee181ba52ed
  2. 1mo ago First seen · 138 lines · 37 tokens per session scan A 270d4e2e57c9

Subscribe to this mod's changes

add-prompt is a skill published in the GitHub repository cyanheads/evals-mcp-server (1 stars, last pushed 4d ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,582 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to add-prompt, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

ai-engineering-toolkit

Overview of six AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

sickn33/agentic-awesome-skills · 47 tokens

prompt-optimization

Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…

langwatch/langwatch · 105 tokens

prompts

Version and manage your agent's prompts with LangWatch Prompts CLI. Use for both onboarding (set up prompt versioning for an entire codebase) and targeted operations (version a specific prompt, create a new prompt version). Supports Python and TypeScript.

langwatch/langwatch · 54 tokens

prompt-regression

Use when the user has changed a prompt (system prompt, RAG template, agent instruction, etc.) and wants to know whether the candidate is better or worse than the baseline. Also use when the user mentions prompt A/B testing, prompt comparison, prompt optimization validation, "did my prompt change help," or prompt…

agentscope-ai/OpenJudge · 86 tokens

prompt-engineering

Use when one prompt must give the same right answer across reruns, models, and pasted-in hostile input: forcing a fixed schema, picking the few-shot set, ordering the prompt blocks, or the inline cases you run while tuning. NOT the agent loop, tools, or retrieval (that is building-agents), NOT a standing CI eval…

ericrisco/rsc-harness · 83 tokens

llm-engineering-expert

Build reliable applications on large language models: prompt design, structured output, evaluation, guardrails, and cost and latency control. Use when the user mentions LLMs, prompts, prompt engineering, few-shot examples, structured or JSON output, function calling, hallucination, model evaluation, token costs…

personamanagmentlayer/pcl · 92 tokens