FlagForge MCP Server

save_writeup

Save CTF writeups as markdown, choosing Thai for human review or English for AI-generated content. Markdown renders headings, code, tables, and images.

Instructions

Save a writeup as markdown. Record Thai for human review, English for AI-generated.

Markdown is rendered on the challenge page — headings, code blocks, tables and images all display. To embed an image:

upload it with upload_artifact → returns an artifact id
reference it in the markdown as

External image URLs (https://...) also render. Do NOT use relative paths like /_astro/... — they will 404 on the FlagForge site.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "challenge_id": "<challenge_id>",
      "language": "<language>",
      "markdown": "<markdown>"
    },
    "name": "save_writeup"
  }
}

Input Schema

Name	Required	Description	Default
`status`	No
`language`	Yes
`markdown`	Yes
`challenge_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 5, 2026

TDQS

A3.6/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden, and it does disclose meaningful behavior: markdown rendering context, the artifact-id image workflow, and a concrete failure mode ('relative paths like /_astro/... will 404'). The critical gap is that it never states whether saving overwrites an existing writeup for the same challenge, which is essential mutation semantics for a save tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded in the first sentence, followed by a numbered image-embedding workflow and a concise 404 warning. Every sentence earns its place, and the list format is scannable. Slightly verbose in the rendering sentence, but overall tight and well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema and no annotations, the description handles the complex parts well: rendering behavior, the two-step artifact workflow, and a known failure mode. But it omits two things an agent needs to call it safely: the meaning of the status enum values, and whether re-saving the same challenge_id replaces the existing writeup. These gaps keep it from being fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds real meaning for language ('Thai for human review, English for AI-generated') and for markdown (rendering rules, image syntax, forbidden paths). However, the status enum (draft/reviewed/final) is completely unexplained, and challenge_id semantics beyond the schema's uuid format are absent — a notable gap for an optional enum field the agent must choose among.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource+format: 'Save a writeup as markdown.' The language mapping ('Thai for human review, English for AI-generated') further clarifies scope and differentiates this from the read-side sibling get_writeup and from save_evidence by resource type. It doesn't name siblings explicitly, so it falls just short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear conditional workflow guidance: 'To embed an image: upload it with upload_artifact → reference it in the markdown,' and notes external URLs as an alternative. The Thai/English instruction tells the agent which language value to use in which scenario. However, it never states when to prefer this over save_evidence or get_writeup, and there are no explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.