skills/create-tooluniverse-skill/assets/skill_template/SKILL.md
--- name: tooluniverse-[domain-name] description: [Complete description of what the skill does, which databases it uses, and when to use it. Include specific trigger phrases like "analyze [domain]", "find [data type]", etc. This description is the primary way Claude determines when to use your skill.] --- # [Domain Name] Analysis [One paragraph overview describing what this skill does, what problems it solves, and what outputs it provides.] ## When to Use This Skill **Triggers**: - "[Trigger
npx skillsauth add mims-harvard/tooluniverse skills/create-tooluniverse-skill/assets/skill_templateInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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[One paragraph overview describing what this skill does, what problems it solves, and what outputs it provides.]
Triggers:
Use Cases:
| Database | Coverage | Strengths | |----------|----------|-----------| | Database 1 | [What it covers] | [What it's best for] | | Database 2 | [What it covers] | [What it's best for] | | Database 3 | [What it covers] | [What it's best for] |
Input → Phase 1: [Name] → Phase 2: [Name] → Phase 3: [Name] → Report
When: [When this phase runs - e.g., "When input_param_1 provided"]
Objective: [What this phase achieves]
TOOL_NAME_1:
parameter1 (type, required/optional): Descriptionparameter2 (type, required/optional): DescriptionTOOL_NAME_2 (Fallback):
When: [Conditions]
Objective: [Goal]
[Similar structure to Phase 1]
[Step-by-step process]
[How to handle different scenarios]
[Similar structure]
When: Always included
Objective: Provide context even when specific phases empty
[Structure similar to above phases]
Progressive Markdown Report:
Required Sections:
Per-Database Subsections:
Phase 1 Results: | Column 1 | Column 2 | Column 3 | | ... | ... | ... |
Phase 2 Results: | Column 1 | Column 2 | Column 3 | | ... | ... | ... |
Critical Parameter Notes (from testing):
| Tool | Parameter | CORRECT Name | Common Mistake |
|------|-----------|--------------|----------------|
| TOOL_NAME_1 | param | ✅ actual_param_name | ❌ assumed_param_name |
| TOOL_NAME_2 | param | ✅ correct_name | ❌ function_name_param |
Response Format Notes:
{status: "success", data: [...]} format{field1: ..., field2: ...}SOAP Tools (if applicable):
operation parameter (e.g., operation="method_name")Input: [Description of typical input]
Workflow: Phase 1 → Phase 3 → Report
Output: [What user gets]
Input: [Description]
Workflow: [Which phases run]
Output: [Result type]
Input: [Multiple inputs]
Workflow: All phases
Output: [Complete analysis]
[Domain] Analysis Skill provides:
Outputs: Markdown report with [description of content]
Best for: [Primary use cases and target users]
tools
Generate the success criteria for a task or question, then review work against them. Given a task, goal, or open-ended question, decompose it into scenarios, evaluation perspectives, and fine-grained weighted YES/NO criteria using the Recursive Expansion Tree (RET) method; if work is supplied, score it criterion-by-criterion and surface what is missing or could be better. Use when asked to self-review or check your own work, judge whether a task is done well or completely, build a definition-of-done or completeness checklist, create an evaluation rubric or grading criteria, score or grade answers to a question, set up an LLM-as-judge rubric, or when the user mentions self-review, completeness check, success criteria, evaluation criteria, scoring rubric, Qworld, or the RET algorithm.
tools
Find the real protein target(s) of a peptide from its sequence — peptide target deorphanization / off-target identification, for ANY target class (GPCR, ion channel, protease, cytokine/growth-factor receptor, enzyme, integrin), not only GPCRs. Use when a peptide has a phenotype but does not bind its hypothesized target, when a peptide binds a target in one species or assay but not another, or to screen candidate targets for an orphan peptide. A target-class router steers a multi-route keyless pipeline (PROSITE/ELM motif, BLAST homology, HGNC/InterPro/GPCRdb/GtoPdb target-family enumeration, OpenTargets phenotype anchor, EnsemblCompara/Alliance cross-species reconciliation) plus optional NVIDIA-NIM co-folding (Boltz2, AlphaFold2-Multimer, OpenFold3) for structural confirmation.
tools
Install or update ToolUniverse in Claude Science — create the conda env, install the tooluniverse pip package, and (re)build the tooluniverse-research skill by fetching the current workflow library from GitHub. Use for first-time setup, upgrading the ToolUniverse version, refreshing the bundled workflows after an upstream release, or reinstalling on a new machine.
tools
Install, set up, verify, update, pin, uninstall, or troubleshoot the ToolUniverse plugin on OpenAI Codex. ALWAYS consult this skill for any of those — don't answer from memory, because the exact marketplace name (mims-harvard/ToolUniverse), the "codex plugin marketplace add" then "codex plugin add -m tooluniverse" flow, Codex's startup auto-upgrade behavior, the uvx tooluniverse MCP server, and the API-key env vars are easy to get wrong. Use it whenever someone wants to get ToolUniverse (or "the 1000+ scientific tools" / "the harvard tools") working on Codex, says the Codex plugin or its tools/skills won't load, hits a uvx or MCP-server startup error, asks how Codex updates it, wants to pin or remove it, or finds it running an old tool version — even if they never say the word "plugin". Not for the Claude Code plugin (use tooluniverse-claude-code-plugin), for running research with the tools, or for authoring new tools or skills.