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IA-QA — 130+ QA & Dev Tools for AI Agents

merge_json

Read-onlyIdempotent

Deep merge two JSON objects. Supports three array strategies: replace (default), concat, or unique (dedup concat). Nested objects are recursively merged — override takes precedence for primitives.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseYesThe base JSON object (merged into) — a JSON string, or the object itself.
overrideYesThe override JSON object (takes precedence) — a JSON string, or the object itself.
array_strategyNoArray merge strategy: replace (default), concat, or unique

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
mergedNo
new_keysNo
total_keysNo
overridden_keysNo

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it as read-only (readOnlyHint: true) and idempotent (idempotentHint: true), so the description's main behavioral contribution is the array strategy detail and recursive merging behavior. This adds valuable context beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. First sentence states purpose and array strategies. Second sentence explains nested object behavior and priority. Every sentence provides essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists (no need to describe return values) and schema covers all parameters, the description's focus on merge behavior and array strategies makes it fairly complete. Could mention that default strategy is replace, which is implied by 'replace (default)'.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds high-level context (recursive merge, override precedence for primitives) but doesn't elaborate on parameter format or edge cases beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Deep merge two JSON objects', specifying the verb (merge), resource (JSON objects), and mode (deep). It distinguishes from siblings like json_diff or flatten_json by focusing specifically on recursive merge with array strategy options.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for merging JSON objects with control over array handling, but does not explicitly state when to prefer this over sibling tools like json_diff or transform_json_array. No guidance on prerequisites (e.g., valid JSON structure) or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0
Disambiguation2/5

Multiple tools overlap significantly: compare_models/llm_fit_finder/model_info/list_llm_models all compare models; similarity_score/embedding_similarity/run_semantic_tests all measure text similarity; detect_secrets/secret_scan/analyze_diff_bugs/pr_gatekeeper all scan for secrets. Descriptions attempt to differentiate, but the boundaries between many tools are unclear, making selection error-prone.

Naming Consistency4/5

The vast majority of tools follow a snake_case verb_noun pattern (validate_email, generate_uuid, parse_csv), making the set mostly predictable. A few notable deviations exist (pr_gatekeeper, llm_fit_finder, cot_analyzer, jira_to_test_suite, needle_haystack_generate) but they are the exception rather than the rule.

Tool Count1/5

With 149 tools, this set is far beyond the 50+ threshold for an extreme mismatch. Even as a general-purpose QA & Dev toolkit, the sheer number overwhelms and exceeds any reasonable scope, making discovery and selection impractical.

Completeness4/5

The toolkit covers an impressively broad range: text processing, LLM evaluation, security auditing, web checks, MCP validation, Jira/Confluence integration, and more. Minor gaps exist, such as missing delete/update for webhooks and Confluence pages, and no create/update for Jira issues, but these are workable around.

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