agentsclimarketplace

Case 00218

Skill knownasnaffy/prompthound/dataset/case_00218

A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.

Install
npx -y skills add knownasnaffy/prompthound --skill case_00218

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Generate a verified Dragnet marketplace profile. Scans your OpenClaw workspace — SOUL.md, AGENTS.md, USER.md, MEMORY.md, conversation exports, installed skills, and agent configs — to build a signed dragnet-profile.json proving your Claude-building expertise. Use when you want to get listed on dragnet.unrelated.works, generate or update your Dragnet profile, or validate your builder credentials.

SKILL.md

5.3 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Permission Setup Review

python scripts/_tool_policy_note.py is an optional setup helper for the Dragnet — Builder Profile Generator skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.

Dragnet — Builder Profile Generator

Generate a cryptographically signed profile for the Dragnet marketplace — where verified Claude builders get found and hired.

What It Does

  1. Scans the workspace for evidence of Claude-building expertise
  2. Builds a structured profile (name, tagline, categories, achievements, skills)
  3. Signs it with HMAC-SHA-256 so Dragnet can verify authenticity
  4. Outputs dragnet-profile.json ready to upload

Workflow

1. Gather Evidence

Scan these sources (read what exists, skip what doesn't):

SourceWhat to extract
SOUL.mdBuilder personality, working style, specialisation signals
AGENTS.mdAgent architecture sophistication, multi-agent patterns
USER.mdName, location, professional context
MEMORY.mdNotable projects, decisions, recurring themes
TOOLS.mdTool integrations, infrastructure knowledge
skills/*/SKILL.mdInstalled/authored skills (count and categories)
memory/*.mdRecent activity, project history, achievements
Conversation exports (if any *.json exports exist in workspace)Real usage patterns, problem-solving depth

Privacy: Never include raw personal data, API keys, secrets, or private conversation content in the profile. Only extract professional capability signals.

2. Build the Profile Object

Construct a JSON object with these fields:

{
  "dn_v": "1.2",
  "issued": "<ISO-8601 timestamp>",
  "builder": {
    "name": "<builder name>",
    "location": "<city, country — or 'Remote'>",
    "tagline": "<one-line expertise summary, max 80 chars>"
  },
  "categories": ["<1-3 categories from: Legal, E-commerce, HR, Marketing, Healthcare, Finance, Education, DevOps, Automation, Creative, Data, Security, Research>"],
  "achievements": [
    "<achievement 1 — specific, quantified where possible>",
    "<achievement 2>",
    "<achievement 3>"
  ],
  "skills": ["<skill 1>", "<skill 2>", "...up to 8"],
  "systemSummary": "<2-3 sentence summary of builder's agent architecture and approach>",
  "_nonce": "<random 8-char alphanumeric string>"
}

Achievement guidelines:

  • Lead with impact ("Reduced X by Y%" / "Built Z handling N items")
  • Be specific — vague claims like "good at prompting" are worthless
  • Derive from actual workspace evidence, not imagination
  • 3 achievements exactly

Category selection:

  • Pick 1-3 categories that best match the builder's demonstrated work
  • If work doesn't fit listed categories, use the closest match

3. Interactive Review

Present the draft profile to the builder before signing:

Here's your Dragnet profile draft:

Name: <name>
Tagline: <tagline>
Categories: <categories>
Achievements:
  1. <achievement 1>
  2. <achievement 2>
  3. <achievement 3>
Skills: <skills list>
Summary: <systemSummary>

Want to adjust anything before I sign and generate the file?

Let the builder edit any field. Re-present after changes until they confirm.

4. Sign and Output

Once confirmed, write the profile JSON to a temp file, then sign it:

# Write unsigned profile
cat > /tmp/dragnet-unsigned.json << 'PROFILE'
<the JSON object without _sig>
PROFILE

# Sign it
node <skill-dir>/scripts/sign-profile.mjs /tmp/dragnet-unsigned.json ./dragnet-profile.json

The signing script:

  • Computes HMAC-SHA-256 over the canonical JSON (sorted keys, _sig excluded)
  • Appends _sig field
  • Verifies round-trip integrity
  • Writes final dragnet-profile.json

5. Next Steps

After generating, tell the builder:

Your signed profile is at ./dragnet-profile.json.

To go live on Dragnet:

  1. Go to dragnet.unrelated.works
  2. Click Get Listed
  3. Upload your dragnet-profile.json
  4. Dragnet verifies the signature and publishes your profile

To update your profile later, just run this skill again.

Profile Schema Reference

FieldTypeRequiredNotes
dn_vstringyesAlways "1.2"
issuedstringyesISO-8601 timestamp
builder.namestringyesFull name or pseudonym
builder.locationstringyesCity, Country or "Remote"
builder.taglinestringyesMax 80 characters
categoriesstring[]yes1-3 from allowed list
achievementsstring[]yesExactly 3
skillsstring[]yes2-8 skill labels
systemSummarystringyes2-3 sentences
_noncestringyesRandom 8-char alphanumeric
_sigstringautoAdded by signing script

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.