Loading ToolBench
Multi-agent AI forge gateway with plugin architecture for sprint planning, code analysis, memory management, and GitHub integration
24 tools with significant structural gaps. Most tools have basic descriptions (50-150 chars) but lack depth on WHEN to use them or prerequisites. Input schemas are present but many parameters lack descriptions or type constraints. Output schemas are largely undocumented, LLMs cannot predict return structure. Error handling is minimal; most tools return generic success/error dicts without recovery guidance. No tool annotations (readOnlyHint, destructiveHint, idempotentHint). Naming is generally verb-first but some tools combine multiple concerns (e.g., 'review_code_architecture' + 'review_architecture_map' are near-duplicates). Parameter descriptions often missing entirely (e.g., 'expand_level' in search_semantic_context has no description in the schema). No pagination support despite tools returning lists. Security: no evidence of input validation, SQL injection guards, or permission checks despite WRITE operations on databases and git repos.
Applies validated multi-line patches safely to target files
Checks AI iteration attempts to prevent infinite circular reasoning
Claim a backlog item for execution by an agent
Mark a sprint as completed and sync documentation
Create a new backlog item in the project
Create a tracked execution plan and log it into ai_sessions for the active sprint
Retrieve the active tool catalog documentation
Output schemas undocumented. Tools return dicts with no documented field structure. LLMs cannot predict what fields to extract or how to chain results to downstream tools.
No input validation or error recovery guidance. Tools accept free-form strings (project_name, query, logic_note) with no constraints, enums, or format specs. Errors return generic dicts without actionable recovery steps.
Duplicate/overlapping tool names. 'review_code_architecture' and 'review_architecture_map' both analyze AST and write docs, LLMs will conflate them. 'search_codebase' and 'search_semantic_context' both search code with nearly identical params.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 50 | 2026-07-28+ | v2 |
Retrieve recent AI session context for a project
Checkout branch locally
Commit safely against master index
Returns modified or uncommitted files
Create Github PR from head to base branch
Log AI session task, logic, and pending work to database
Fetch past AI session walkthroughs/plans.
Release a claimed backlog item back to unclaimed state
Review and generate architecture map documentation
Analyze project AST and generate architecture documentation
Executes isolated Python code snippet in RAM sandbox to test logic
Search codebase using vector embeddings for semantic code search
Search vector database for past decisions and logic notes for a project
Search semantic code context for a project with configurable expansion levels
Store project logic notes in vector database for future reference
Update an existing backlog item
Validate Python code syntax using AST parser before applying patches
No pagination support. Tools returning lists (search_codebase limit=5, search_past_decisions limit=3) have no offset/cursor or total_count. Large result sets will blow context window.
No tool annotations. WRITE operations (store_project_memory, apply_safe_patch, git_local_commit, create_backlog_item) lack destructiveHint. READ-ONLY tools lack readOnlyHint. Agents cannot distinguish safe from risky calls.