Tool Composition and Discovery Design
Tools should compose like Unix pipes, not like a chain of command. That needs three properties across the set: consistent shapes so one output feeds the next input, batch support so the agent does not loop one item at a time, and multiple abstraction levels so the agent can pick the granularity the task needs. It also needs the agent to be able to find the right tool without trial and error.
Procedure
- Map the current set: every tool, its type, and the sequences agents actually run (from traces, not from intent).
- Find bundle candidates: sequences repeated across runs with no branching between steps.
- Find batch candidates: the same tool called in a loop over a list.
- Find ladder gaps: capabilities with only a raw low-level tool and no intent-level tool, or the reverse.
- Add preview modes to every destructive or costly command.
- Design discovery: dependency hints in descriptions, a registry or search tool once the set is large, layered schema exploration for data sources.
- Prune: merge near-duplicates and retire tools with no traffic. Fewer, better-described tools beat many similar ones.
Rules with examples
Offer the capability at more than one altitude (Abstraction Ladder)
low execute_query(sql) full control, expert use
mid search_records(table, filters) structured, safe
high find_customers_like(description) intent-level, does the work
Each rung has a stated use case; higher rungs call lower ones internally; descriptions say when to use which. Do not ship only the low rung and expect the agent to compose it correctly every time.
Bundle the sequence the agent always runs (Task Bundle)
search_users then open_dm then send_message becomes dm_user(name, message).
Name the bundle after the task, not the steps. Handle intermediate failures inside the
bundle and return a composite result that reports each step. Keep the atomic tools
available for edge cases, and say in the bundle's description that it replaces the
sequence.
Accept lists (Batch Operation)
Any tool the agent calls per item over a list gets a batch form: an array input, a
documented maximum batch size, per-item results with status, and a partial-success
report (see tool-design-output). Batch the upstream calls internally where the API
allows. Decide up front whether a batch is all-or-nothing or partial, and say which.
Explore before executing (Operation Mode)
Give commands a mode parameter that defaults to the safest option:
explore list what the tool could do here, read-only
preview show exactly what would change, no side effects
dry_run validate inputs without executing
execute perform the action
Return the same result structure in every mode so the agent can compare a preview to
the real run. A schema mode that returns the upstream's complex input shape is useful
when the shape cannot be expressed in the tool interface.
Make the sequence explicit when it matters (Tool Chain)
For multi-step processes with a fixed order, define the chain as ordered steps with data passing between them and checkpoints for resume. A chain is a specification the agent follows, or a single orchestrated tool that runs it; either way the order is not left to inference.
Fan out, then merge (Scatter-Gather Tool)
A tool that consults several sources queries them in parallel, merges the results into one canonical shape, and reports per-source status so a failed source degrades the result rather than failing it.
Discovery: how the agent finds the right tool
Say what to call first (Dependency Hint)
Descriptions and parameter docs name prerequisites ("userId: if you only have an
email, call search_users first"), follow-ups ("after this, get_user verifies the
change"), and alternatives ("if this fails, try send_email"). Repeat the hint in the
error the tool returns when the prerequisite is missing.
Catalog the set when it is large (Tool Registry, Capability Matching)
Past roughly twenty tools, the model can no longer hold every definition in context.
Provide a list_available_tools(category) registry with name, description, category,
and auth requirements, and a find_tool_by_intent(intent) search that ranks tools by
semantic match with confidence and usage examples. Keep the must-use tools always
loaded and let the long tail be discovered.
Reveal structure in layers (Schema Explorer)
For data sources, do not dump the full schema. Layer it: list_tables(), then
describe_table(name), then sample_rows(table, limit), then get_query_hints(table).
Each layer's description names the next.
Check before relying (Health Check)
A fast (sub-second) check_service_health(service) returns healthy, degraded, or
unavailable with specific reasons, so the agent does not spend turns on a dead backend.
Cache the status briefly.
Across the system
- Tool Gateway: one entry point routes to many backends and aggregates discovery, so the agent sees one consistent set.
- Tool Adapter: wrap a legacy or awkward API in a clean tool: LLM-friendly description, constrained inputs, shaped output. The adapter hides the legacy shape entirely.
- Canonical Tool Model: shared
User,Task,Eventshapes and field names across every tool, mapped to and from each backend. - Tool Versioning: version in the name (
send_email_v2) or metadata, run versions in parallel during migration, and deprecate with a migration note in the old tool's description.
Anti-patterns
- Thirty atomic tools and no bundle for the sequence 80% of runs perform.
delete_fileswith no preview mode.- Two tools that differ only in one optional parameter.
- A registry that lists tools without their auth requirements or categories.
- A composite tool built before any trace showed the sequence being used.
- A migration that changes a tool's behavior in place instead of versioning it.
On Runtype
- Tool count and residency. A dispatch carries at most 50 runtime tools. At 20
the platform partitions them into a hot set plus a
tool_searchmeta-tool. Pin the must-use tools withconfig.tools.toolSearch.alwaysLoaded(oralwaysLoaded: trueon the tool), raise or lower the cut withtoolSearch.threshold, or settoolSearch.enabled: falseto force every tool into context. Descriptions drive both model choice and search ranking. - Task bundle and tool chain. A flow is the platform's explicit chain: fixed step
order, data passing, per-step error handling. Expose it as one tool
(
toolType: "flow") when the agent should run the whole sequence as a single call. - Abstraction ladder. Built-in and Orthogonal catalog tools are the low rung,
customandexternaltools the middle, flows and subagents the top. Subagents have their own caps; readget_platform_documentation(topic="subagent-delegation"). - Operation mode. A
tool-callflow step runs a catalog tool deterministically with no approval gate, so a preview mode must be a distinct tool or amodeparameter; do not rely on the gate to make a step safe. - Registry and discovery.
list_toolscovers saved tools,discover_mcp_server_toolsan MCP server, andget_platform_documentation(topic="builtin-tools")the catalog. Atool-callstep that names a catalog id nobody answers to is rejected asTOOL_CALL_STEP_UNKNOWN_CATALOG_TOOL. - Versioning. Agents and flows are versioned (
publish_agent_version,publish_flow_version); a tool behavior change ships behind a new published version rather than in place.