Loading ToolBench
A centralized, Hugging Face-hosted MCP server for discovering and executing community skills.
9 tools with significant definition gaps. All tools have descriptions (10-200 chars, mostly adequate), but input schemas lack critical details: no enums for constrained values (e.g., target_style, framework, issue_type), no min/max bounds on numeric params, no explicit type declarations for array items. Parameters like 'repo_url' vs 'repo_path' are mutually exclusive but not documented. Output schemas are completely absent, LLMs cannot predict what these tools return. Error handling is not visible in tool definitions. Two write tools (jira-ticket, servicenow-ticket) expose credentials via environment variables (correct pattern) but lack permission gates or audit trail declarations. Naming is generally clear (verb_noun style), but descriptions lack WHEN/WHY context and dependency hints.
Run change-impact analysis. Inputs (provide a repo source): repo_url: public git URL to shallow-clone and analyse (web-friendly), OR repo_path: a local repository root the server can read. changed_files: list of changed file paths (relative to the repo). base_branch: base branch for contract comparison (default "main").
Create a Jira issue via the Jira Cloud REST API. Requires JIRA_BASE_URL, JIRA_EMAIL, and JIRA_API_TOKEN environment variables.
Analyse a remote repo URL or a local repo path (exactly one). Remote mode: given a repo_url (github.com), clones the repo and runs the full static-analysis pipeline (System Design Document + report + evaluation). Local mode: given a repo_path (a directory the server can read), inventories languages, entry points, and modules and returns spec + architecture scaffolds.
Create a ServiceNow incident via the Table API. Requires SERVICENOW_INSTANCE, SERVICENOW_USER, and SERVICENOW_PASSWORD environment variables.
Validate artifacts against governance rules; emit an audit. Checks for required artifacts (spec.md, plan.md, tasks.yaml, tests, architecture.md, adr) and spec sections (overview, requirements, acceptance, out of scope).
No output schemas documented. LLMs cannot predict return types, forcing them to guess what fields are available for downstream tool chaining. This breaks composition patterns.
Mutually exclusive parameters (repo_url vs repo_path, frameworks array) lack explicit documentation. LLMs will pass both or neither, causing ambiguous failures.
Constrained parameters lack enums. 'target_style' accepts microservices|modular-monolith|serverless but is defined as free-form string. 'framework' and 'issue_type' similarly unconstrained. LLMs hallucinate invalid values.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 47 | 2026-07-28+ | v2 |
Convert a specification into a tasks.yaml backlog. Generates user stories with design, implementation, and test tasks.
Produce a test strategy and starter stubs for modules. Generates test plans and code stubs for pytest, jest, and playwright frameworks.
Produce a target architecture + migration plan. Generates migration plans for microservices, modular-monolith, or serverless architectures.
Plan a legacy UI migration to a modern component framework. Generates component inventory and migration plan for React or other frameworks.
Numeric parameters lack bounds. 'num_stories' (1-12) and array sizes are unbounded in schema. LLMs can pass 0, negative, or absurdly large values.
Write tools (jira-ticket, servicenow-ticket) lack permission gates, confirmation steps, or dry-run support. No audit trail declarations. Agents can create tickets without safeguards.