Setup guide

Spend approvals with the policy check done first - on Town

The $19 Spend Request Agent runs on Town as three plain-text files: set it up once in Town, approve a sample-data test, then trigger each run with the usage prompt and this run's inputs.

What the Spend Request Agent does

Town already runs your inbox and calendar - this agent becomes one more job it owns. It normalizes incoming spend requests and runs your policy and evidence checks: request, amount, policy check, evidence, approver and status. Approvals become one review, not a reconstruction.

Spend requests arrive by email, chat and the occasional hallway ask. Policy checks happen in someone's head, and audit season reconstructs decisions nobody wrote down.

Where the three files go in Town

Share the three files with Town and ask it to keep skill.md as the standing rules for the job, then run the setup prompt and approve the fictional-data test. Town's email and calendar focus pairs well with agents whose output is a draft, a schedule or a follow-up queue.

What a run looks like on Town

A run looks like this: you ask Town to run spend-approvals with this run's inputs, and it works through the standing rules you gave it. The output - it normalizes incoming spend requests and runs your policy and evidence checks: request, amount, policy check, evidence, approver and status - is prepared for your review alongside the rest of your delegated work.

Setup, step by step

  1. Share skill.md, setup-prompt.txt and usage-prompt.txt with Town and ask it to keep the skill as the standing rules for the job (for example: spend approvals).
  2. Run the setup prompt; the agent runs spend-approvals on fictional sample data first - approve that test before real work.
  3. Town's inbox-and-calendar focus pairs best with agents whose output is a draft, a schedule or a follow-up queue.
  4. Trigger each real run with one message and this run's inputs.

Honest limits on Town

Town is inbox-and-calendar centric and its feature set is young; confirm its current file and memory handling in Town's own documentation before a big setup.

Questions people ask

Does the Spend Request Agent work on Town?

Yes - the agent is three plain-text files, and on Town they live in Town. The four setup steps below are the whole job: Share skill.md, setup-prompt.txt and usage-prompt.txt with Town and ask it to keep the skill as the standing rules for the job (for example: spend approvals). Then run the setup prompt; the agent runs spend-approvals on fictional sample data first - approve that test before real work.

What does the Spend Request Agent produce on Town?

It normalizes incoming spend requests and runs your policy and evidence checks: request, amount, policy check, evidence, approver and status. Town prepares it as part of your delegated queue; you approve before use. Every run waits for your approval before anything is sent, spent, published or scheduled.

Is this affiliated with Town?

No. AI Agent Skills is an independent store. We are not affiliated with, endorsed by, or sponsored by Town or its makers. Platform names belong to their owners; capabilities change, so check Town's current documentation.

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AI Agent Skills is an independent store, not affiliated with Town or its makers. Platform names belong to their owners.