Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Decompose Mcp
Decompose any text into classified semantic units — authority, risk, attention, entities. No LLM. Deterministic.
skill openclawclawhub Free
Decompose any text into classified semantic units — authority, risk, attention, entities. No LLM. Deterministic.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, claw.json
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.2
Provenance
- Publisher
- echology-io
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Decompose
Decompose any text or URL into classified semantic units. Each unit gets authority level, risk category, attention score, entity extraction, and irreducibility flags. No LLM required. Deterministic. Runs locally.
1. Install
pip install decompose-mcp
2. Configure MCP Server
Add to your OpenClaw MCP config: { "mcpServers": { "decompose": { "command": "python3", "args": ["-m", "decompose", "--serve"] } } }
3. Verify
python3 -m decompose --text "The contractor shall provide all materials per ASTM C150-20."
decompose_text
Decompose any text into classified semantic units. Parameters: text (required) — The text to decompose compact (optional, default: false) — Omit zero-value fields for smaller output chunk_size (optional, default: 2000) — Max characters per unit Example prompt: "Decompose this spec and tell me which sections are mandatory" Returns: JSON with units array. Each unit contains: authority — mandatory, prohibitive, directive, permissive, conditional, informational risk — safety_critical, security, compliance, financial, contractual, advisory, informational attention — 0.0 to 10.0 priority score actionable — whether someone needs to act on this irreducible — whether content must be preserved verbatim entities — referenced standards and codes (ASTM, ASCE, IBC, OSHA, etc.) dates — extracted date references financial — extracted dollar amounts and percentages heading_path — document structure hierarchy
decompose_url
Fetch a URL and decompose its content. Handles HTML, Markdown, and plain text. Parameters: url (required) — URL to fetch and decompose compact (optional, default: false) — Omit zero-value fields Example prompt: "Decompose https://spec.example.com/transport and show me the security requirements"
What It Detects
Authority levels — RFC 2119 keywords: "shall" = mandatory, "should" = directive, "may" = permissive Risk categories — safety-critical, security, compliance, financial, contractual Attention scoring — authority weight x risk multiplier, 0-10 scale Standards references — ASTM, ASCE, IBC, OSHA, ACI, AISC, AWS, ISO, EN Financial values — dollar amounts, percentages, retainage, liquidated damages Dates — deadlines, milestones, notice periods Irreducibility — legal mandates, threshold values, formulas that cannot be paraphrased
Use Cases
Pre-process documents before sending to your LLM — save 60-80% of context window Classify specs, contracts, policies, regulations by obligation level Extract standards references and compliance requirements Route high-attention content to specialized analysis chains Build structured training data from raw documents
Performance
~14ms average per document on Apple Silicon 1,000+ chars/ms throughput Zero API calls, zero cost, works offline Deterministic — same input always produces same output
Security & Trust
Text classification is fully local. The decompose_text tool performs all processing in-process with no network I/O. No data leaves your machine. URL fetching performs outbound HTTP requests. The decompose_url tool fetches the target URL, which necessarily involves network I/O to the specified host. This is why the skill declares the network permission in claw.json. If you do not need URL fetching, you can use decompose_text exclusively with no network access required. SSRF protection. URL fetching blocks private/internal IP ranges before connecting: 0.0.0.0/8, 10.0.0.0/8, 100.64.0.0/10, 127.0.0.0/8, 169.254.0.0/16, 172.16.0.0/12, 192.168.0.0/16, ::1/128, fc00::/7, fe80::/10. The implementation resolves the hostname via DNS before connecting and checks all returned addresses against the blocklist. See src/decompose/mcp_server.py lines 19-49. No API keys or credentials required. No external services are contacted except when using decompose_url to fetch user-specified URLs. Source code is fully auditable. The complete source is published at github.com/echology-io/decompose. The PyPI package is built from this repo via GitHub Actions (publish.yml) using PyPI Trusted Publishers (OIDC), so the published artifact is traceable to a specific commit.
Resources
Source Code (GitHub) — full source, auditable PyPI — published via Trusted Publishers Documentation Blog: When Regex Beats an LLM Blog: Why Your Agent Needs a Cognitive Primitive
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Config
- SKILL.md
- claw.json