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Save a durable memory or handoff

memory_save

Write a durable note to the shared Tango memory vault so the next agent — in any harness — can pick it up. Use it for handoffs between tools ('continue the auth migration in Codex'), for context that outlives one session, and for anything a teammate would need to re-derive otherwise. Scope it to a client and, where relevant, a project or task; nothing is visible outside that workspace. Memory is unreviewed context, not policy: readers must verify important claims before acting on them. For durable team standards use update_client_context or log_project_decision instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesThe memory itself, in markdown.
tagsNoFree-form tags to search on later.
titleYesA short, searchable title.
clientNoClient/workspace name or @handle this memory belongs to.
task_idNoThe task this memory came out of, if any.
client_idNo
project_idNoNarrow the memory to one project.
source_harnessNoThe harness writing this memory.
target_harnessNoHarness this handoff is addressed to (e.g. 'codex', 'claude'). Leave empty for a general memory.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations only provide readOnlyHint=false and destructiveHint=false. The description adds meaningful behavioral context beyond those: memory is unreviewed context, readers must verify claims, nothing is visible outside the workspace, and memory persists across harnesses. This is valuable transparency not available in structured metadata.

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?

Four sentences with no filler. It front-loads the core action, then gives use cases, scoping guidance, a trust caveat, and alternatives—each sentence earns its place.

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 has 9 parameters, no output schema, and is a cross-agent write operation, the description covers the essential context: what is stored, who consumes it, how to scope it, the trust boundary, and when to use a different tool. Nothing critical an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is high at 89%, so the schema itself documents most parameters. The description adds extra meaning by explaining how to scope memories ('Scope it to a client and, where relevant, a project or task') and by tying the handoff concept to harness and cross-agent visibility, which helps an agent interpret fields like client, project_id, task_id, source_harness, and target_harness.

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 the verb and resource: 'Write a durable note to the shared Tango memory vault.' It also distinguishes itself from siblings by emphasizing persistence across harnesses and sessions, and explicitly names alternatives (update_client_context, log_project_decision) for different use cases.

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?

The description gives concrete when-to-use scenarios: handoffs between tools, context that outlives one session, and anything a teammate would need to re-derive. It also provides explicit exclusions by directing durable team standards to update_client_context or log_project_decision instead.

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

A3.7/5.0
Disambiguation3/5

Most tools target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.

Tool Count2/5

At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.

Completeness4/5

The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.

Resources