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roam_datomic_query

Execute custom Datomic queries on your Roam graph for advanced data retrieval beyond standard search. Use complex boolean logic, regex filtering, custom sorting, and proximity search to extract precisely the data you need.

Instructions

Execute a custom Datomic query on the Roam graph for advanced data retrieval beyond the available search tools. This provides direct access to Roam's query engine. Note: Roam graph is case-sensitive.

Optimal Use Cases for roam_datomic_query:

  • Advanced Filtering (including Regex): Use for scenarios requiring complex filtering, including regex matching on results post-query, which Datalog does not natively support for all data types. It can fetch broader results for client-side post-processing.

  • Highly Complex Boolean Logic: Ideal for intricate combinations of "AND", "OR", and "NOT" conditions across multiple terms or attributes.

  • Arbitrary Sorting Criteria: The go-to for highly customized sorting needs beyond default options.

  • Proximity Search: For advanced search capabilities involving proximity, which are difficult to implement efficiently with simpler tools.

List of some of Roam's data model Namespaces and Attributes: ancestor (descendants), attrs (lookup), block (children, heading, open, order, page, parents, props, refs, string, text-align, uid), children (view-type), create (email, time), descendant (ancestors), edit (email, seen-by, time), entity (attrs), log (id), node (title), page (uid, title), refs (text). Predicates (clojure.string/includes?, clojure.string/starts-with?, clojure.string/ends-with?, <, >, <=, >=, =, not=, !=). Aggregates (distinct, count, sum, max, min, avg, limit). Tips: Use :block/parents for all ancestor levels, :block/children for direct descendants only; combine clojure.string for complex matching, use distinct to deduplicate, leverage Pull patterns for hierarchies, handle case-sensitivity carefully, and chain ancestry rules for multi-level queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe Datomic query to execute (in Datalog syntax). Example: `[:find ?block-string :where [?block :block/string ?block-string] (or [(clojure.string/includes? ?block-string "hypnosis")] [(clojure.string/includes? ?block-string "trance")] [(clojure.string/includes? ?block-string "suggestion")]) :limit 25]`
inputsNoOptional array of input parameters for the query
regexFilterNoOptional: A regex pattern to filter the results client-side after the Datomic query. Applied to JSON.stringify(result) or specific fields if regexTargetField is provided.
regexFlagsNoOptional: Flags for the regex filter (e.g., "i" for case-insensitive, "g" for global).
regexTargetFieldNoOptional: An array of field paths (e.g., ["block_string", "page_title"]) within each Datomic result object to apply the regex filter to. If not provided, the regex is applied to the stringified full result.
graphNoTarget graph key from ROAM_GRAPHS config. Defaults to ROAM_DEFAULT_GRAPH. Only needed in multi-graph mode.
write_keyNoWrite confirmation key. Required for write operations on non-default graphs when write_key is configured.
Behavior4/5

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

Despite no annotations, the description discloses case-sensitivity, lists namespaces and attributes, predicates, aggregates, and tips. It doesn't explicitly state that it's read-only (likely safe), but the context implies data retrieval. Lacks details on error handling or performance, but overall transparent.

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

Conciseness4/5

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

The description is long but well-structured with headings, bulleted lists, and an example. It front-loads the primary purpose and then provides layered detail. A few sentences could be trimmed, but overall clear and organized.

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 complexity (custom query language, multiple parameters with dependencies, no output schema), the description is remarkably complete. It covers use cases, data model, predicates, aggregates, and practical tips, leaving little ambiguity for an AI agent.

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

Parameters5/5

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

Schema coverage is 100% but description adds an example query, explains regex filter behavior (client-side, target fields), graph/write_key context, and includes a tip section. This significantly enriches the meaning of parameters beyond the schema.

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?

Description clearly states it executes a custom Datomic query for advanced data retrieval beyond available search tools. It distinguishes itself from sibling tools like roam_search_by_text by targeting complex, custom queries.

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

Usage Guidelines5/5

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

Explicitly lists optimal use cases (advanced filtering, regex, complex boolean logic, arbitrary sorting, proximity search) with formatting that contrasts with simpler tools. Provides actionable guidance on when to use this tool over others.

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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