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Get Pending Approvals

get_pending_approvals
Read-only

Covers four channels, each pending row bucketed by action-type category exactly as the page groups them: LinkedIn connection requests / messages / follows / post engagement, emails, gifts, and manual actions. Same-post comment+reaction rows collapse into one engagement item, matching the page. A gift item carries the order its card shows (product_url, max_price_usd, shipping_address, with the note as its summary) and an error; the user completes any missing piece on the card before approving it. max_price_usd is the most the item may cost including tax and shipping; approving charges the owner's card for gifts the order's actual total, at most max_price_usd, plus about $3.30 + 2.9% in fees on top. error is blank unless the user approved the card and the order was refused: it then gives the reason, and the card waits for the user to fix the order and approve it again. owner_has_gift_card is false when the agent's owner has saved no card for gifts; approving then orders nothing until the owner adds one under Settings → Billing. Sequence-produced items (LinkedIn, email, and a manual or gift step queued by its flow node) carry node_id/node_label naming the campaign-flow node that authored them — null for items created outside a sequence. A manual item also carries completion_criteria: how to advance the prospect once the user reports what they did. Cross-agent for the owner; for one agent's items, pass agent_id, and for one step of its flow, also pass that step's bucket and keep the items carrying its node_id. A shared operator sees only the shared agent.

Bounded by default so an approval-gated campaign holding thousands of drafts doesn't return every full message. The default gives per-bucket/per-agent counts plus a short preview per bucket (first few items); pass bucket to page that one bucket's full item list. A bucket's preview_truncated (or count exceeding the preview) tells you to drill in. By default (no bucket), a dict {'pending': {'total': int, 'buckets': [{'bucket', 'title', 'count', 'preview_truncated': bool, 'agents': [{'agent_id', 'agent_title', 'count'}], 'preview': [item, ...]}]}, 'recently_resolved': {'window_days': int, 'total': int, 'items': [...]}, 'recently_shelved': {'window_days': int, 'total': int, 'items': [...]}}. The preview holds the bucket's first few full items. Recently-resolved lists only rows with a transition timestamp — manual done/dismissed, LinkedIn/email sent; cancelled or rejected drafts don't appear there. Recently-shelved lists rows the shelf-life sweep shelved (an unstarred draft that aged past its approval window); each item's target_provider_id is the prospect handle for person-addressed LinkedIn drafts (connection_request / message / inmail / follow) so a swept draft matches back to a prospect — blank for comment/reaction (post-addressed) and for email. Drill-down (bucket set): {'bucket', 'title', 'count', 'offset', 'limit', 'truncated': bool, 'items': [item, ...]} — full-text items, newest-first; count is the whole bucket, truncated means more beyond this page (re-call with offset += limit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bucketNoDrill into one bucket for its full-text items, paged. One of 'email', 'linkedin_invite', 'linkedin_message', 'linkedin_follow', 'engagement', 'gift', 'manual'. Omit for the bounded counts+preview.
offsetNoRows to skip in drill-down mode (default 0); re-call with `offset += limit` while `truncated` is true. Ignored without `bucket`.
agent_idNoScope every section to one agent's items. Omit for every agent.
on_behalf_ofNoA teammate's email (one with team actions turned on), or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.
resolved_within_daysNoRecency window for the recently-resolved section (default 7). Only used in the default (no-`bucket`) mode.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / on_behalf_of / description
      Previous value: -"Read a consented teammate's pending approvals instead of\nyour own — pass their email. Gated on that teammate's act-on-behalf\nsetting (stricter than conversation sharing); a teammate who hasn't\ngranted it is rejected. Omit for your own.\nOr pass an agency client's email, from list_agency_clients, to run the call in that client's account, where none of the teammate limits above apply."New value: +"A teammate's email (one with team actions turned on), or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
  2. Changed4 schema fields changed
    • removedInput schema / properties / as_teammate
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "string"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "description": "Read a consented teammate's pending approvals instead of\nyour own — pass their email. Gated on that teammate's act-on-behalf\nsetting (stricter than conversation sharing); a teammate who hasn't\ngranted it is rejected. Omit for your own."
      -}
    • changedInput schema / properties / bucket / anyOf
      Previous value: -[
      -  {
      -    "enum": [
      -      "email",
      -      "linkedin_invite",
      -      "linkedin_message",
      -      "linkedin_follow",
      -      "engagement",
      -      "reddit",
      -      "gift",
      -      "manual"
      -    ],
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "enum": [
      +      "email",
      +      "linkedin_invite",
      +      "linkedin_message",
      +      "linkedin_follow",
      +      "engagement",
      +      "gift",
      +      "manual"
      +    ],
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • changedInput schema / properties / bucket / description
      Previous value: -"Drill into one bucket for its full-text items, paged. One of\n'email', 'linkedin_invite', 'linkedin_message', 'linkedin_follow',\n'engagement', 'reddit', 'gift', 'manual'. Omit for the bounded counts+preview."New value: +"Drill into one bucket for its full-text items, paged. One of\n'email', 'linkedin_invite', 'linkedin_message', 'linkedin_follow',\n'engagement', 'gift', 'manual'. Omit for the bounded counts+preview."
    • addedInput schema / properties / on_behalf_of
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Read a consented teammate's pending approvals instead of\nyour own — pass their email. Gated on that teammate's act-on-behalf\nsetting (stricter than conversation sharing); a teammate who hasn't\ngranted it is rejected. Omit for your own.\nOr pass an agency client's email, from list_agency_clients, to run the call in that client's account, where none of the teammate limits above apply."
      +}
  3. Changed1 schema field changed
    • addedInput schema / properties / agent_id
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Scope every section to one agent's items. Omit for every agent."
      +}
  4. Changed2 schema fields changed
    • changedInput schema / properties / bucket / anyOf
      Previous value: -[
      -  {
      -    "enum": [
      -      "email",
      -      "linkedin_invite",
      -      "linkedin_message",
      -      "linkedin_follow",
      -      "engagement",
      -      "reddit",
      -      "manual"
      -    ],
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "enum": [
      +      "email",
      +      "linkedin_invite",
      +      "linkedin_message",
      +      "linkedin_follow",
      +      "engagement",
      +      "reddit",
      +      "gift",
      +      "manual"
      +    ],
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • changedInput schema / properties / bucket / description
      Previous value: -"Drill into one bucket for its full-text items, paged. One of\n'email', 'linkedin_invite', 'linkedin_message', 'linkedin_follow',\n'engagement', 'reddit', 'manual'. Omit for the bounded counts+preview."New value: +"Drill into one bucket for its full-text items, paged. One of\n'email', 'linkedin_invite', 'linkedin_message', 'linkedin_follow',\n'engagement', 'reddit', 'gift', 'manual'. Omit for the bounded counts+preview."
  5. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With readOnlyHint=true already covering the safety profile, the description adds substantial behavioral context: results are bounded by default with counts+preview, preview_truncated signals drill-in, gift items can carry an error after a refused order, approving charges the owner's card up to max_price_usd plus ~$3.30 + 2.9% fees, and a shared operator only sees the shared agent. These are non-obvious operational traits that go well beyond the annotation.

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?

Front-loaded with a summary tag and organized by mode (default vs drill-down), with the returns block clearly delineated. It is long and dense — the gift fee arithmetic is borderline — but nearly every sentence conveys decision-relevant behavior rather than filler.

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?

Despite no formal output schema, the description fully specifies both return shapes (default rollup vs bucket drill-down), the meaning of count/truncated/preview_truncated/offset, and edge cases like target_provider_id mapping and cancelled-vs-sent resolution. An agent has everything needed to call and interpret this correctly.

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 100%, so the baseline is 3, but the description adds meaningful interplay semantics: passing bucket switches to paged full-text drill-down while omitting it returns bounded counts+preview, offset is re-called as offset += limit while truncated, and agent_id can be combined with bucket/node_id to isolate one flow step. This goes beyond the per-parameter schema text.

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?

States a specific verb and resource ('List everything waiting on the user — the same pending-approval rollup the home Approvals page renders') and scopes it precisely to the pending/resolved/shelved rollup. An agent can distinguish this from siblings like get_outreach_approval or request_user_action without opening any schema.

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?

Gives explicit usage contexts: answering 'what's waiting on me?', verifying a request_user_action was handled, checking whether a draft was shelved, or before re-flagging a prospect. It also explains scoping (cross-agent, agent_id, bucket/node_id for one flow step). It stops short of naming a direct alternative tool to prefer instead, so it is clear context without explicit exclusions.

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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