ThinAir Data

show_locks

Read-only

List active sessions + blocking locks. Uses the dialect's own system view — pg_stat_activity on postgres, information_schema.processlist on mysql, sys.dm_exec_requests joined with sys.dm_tran_locks on mssql. No dialect arg needed — inferred from the connection. Required privileges (per dialect): postgres — pg_read_all_stats role membership (or be the role that owns the queries; otherwise you only see your own session); mysql — PROCESS privilege; mssql — VIEW SERVER STATE. If the role lacks the privilege the tool returns a clean Query blocked by security policy error rather than partial data — grant the role above and retry. RDS/Aurora/Azure managed PostgreSQL: pg_read_all_stats is grantable but not on by default. [BUILD tier]

Input Schema

TableJSON Schema

Name	Required	Description	Default
`connection`	No	Target connection name from this tenant's inventory. Call `list_connections` to see every name + dialect, then match semantically to the user's intent (e.g. 'analytics' → a connection named `-analytics-`; 'prod' → a connection with `prod-` prefix). If the user didn't specify, use the tenant's default (first added). Do not invent names — resolve from `list_connections` output.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`meta`	No
`display`	No
`summary`	No
`insights`	No

TDQS

A4.5/5.0

Behavior5/5

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

The description goes well beyond annotations by disclosing per-dialect system views, required privileges (pg_read_all_stats, PROCESS, VIEW SERVER STATE), and the clean 'Query blocked by security policy' error instead of partial data. This level of disclosure is exceptional.

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 front-loaded with the core purpose, then efficiently structured into dialect details, privileges, and error behavior. Each sentence carries meaningful information; the only minor extra is the '[BUILD tier]' tag.

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

Completeness5/5

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

Given the tool's multi-dialect complexity, the description covers the essential behavioral aspects: which system views are used, privilege requirements per dialect, error behavior, and the managed PostgreSQL caveat. An output schema exists, so return values needn't be described.

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?

The tool's description text itself adds no parameter details, but the input schema provides 100% coverage with a rich description of the `connection` parameter, including resolution via `list_connections`. Therefore baseline 3 is appropriate.

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 opens with 'List active sessions + blocking locks,' a specific verb+resource statement that clearly distinguishes it from sibling query tools like query_sql or explain_query. It also specifies dialect-specific system views, leaving no ambiguity about scope.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool—whenever session or blocking lock information is needed—and notes that no dialect argument is required. It lacks explicit exclusions or direct alternative references, but the prerequisites and error handling give adequate usage guidance.

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

All ThinAir Data tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0

Disambiguation4/5

Each tool targets a distinct resource/action, though some overlap exists between analyze_table and data_profile (both profile tables) and between pii_scan and configure_allowlist (both deal with PII). Clear descriptions and separation of quick vs. full analysis mitigate confusion.

Naming Consistency3/5

Most tools follow verb_noun (add_connection, describe_schema, generate_migration), but a notable minority use noun phrases (data_profile, pii_scan, query_firewall, saved_queries, quota, impact_analysis). This mixed convention creates inconsistency, though the naming is still readable.

Tool Count3/5

26 tools is slightly over the 16-25 heavy threshold, but each tool addresses a distinct need across connection management, querying, analysis, security, and performance. While the count feels high, the breadth justifies it; however, it's approaching the 'too many' range.

Completeness5/5

The tool set covers the full lifecycle: connections (add/remove/list/test), querying (query_sql, saved_queries, cross_db_query), schema exploration/migration (describe_schema, generate_migration, impact_analysis), data quality/compliance (analyze_table, data_profile, pii_scan), performance (explain_query, optimize_query, show_locks), and monitoring (watch_table, detect_anomalies). Any gaps are minor, such as no update_connection, but that's not a core need.

Resources

Need Help?