Account Signals logo

Account Signals

Organization
Nimbleway
account-signals

Lists what changed at an account since a date: funding, exec moves, launches, pricing changes and hiring pushes, each dated and cited, using the Nimble `account-signals` agent template on live web data. Use when the user says "what changed at", "buying signals", "track my accounts", "any news on my accounts since", "trigger events", "signals for", or arrives from a Nimble use-case page. Interviews the user for the inputs, shows quick search results first, then runs the template at medium and high effort and shows each result as it arrives. Do NOT use for a full company brief (use account-brief) or for investment holdings (use portfolio-monitoring).

Overview

PublisherNimbleway
Repositoryagent-skills
Skill nameaccount-signals
Stars
61
Forks
19
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Nimbleway on GitHub. Read the source before you install it.

Installation

Install the Account Signals AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Nimbleway/agent-skills/tree/main/skills/account-signals
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Nimbleway/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/account-signals .claude/skills/account-signals
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Account Signals in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Account Signals on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Account Signals is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Account signals

Lists what changed at an account since a date: funding, exec moves, launches, pricing changes and hiring pushes, each dated and cited.

User request: $ARGUMENTS

What the user gets

Only events dated after the since date, each with date, type, headline, summary and source. If nothing changed, an empty list and the sources it checked.

Agent template

This skill runs the Nimble gallery template account-signals. The agent's instructions, sources and output schema live in the template. Do not rewrite them in the run.

Effort is the user's choice. By default this skill runs it twice, at medium (2-4 minutes, $0.10) and high (5-15 minutes, $0.50), so the user sees results early and the full result later. The template's own default is medium. If the user asks for a specific effort (low, medium, high, x-high or max), run only that one.

Flow

The user should never wait minutes with nothing on screen. Work in three steps and show a progress line at the start of each:

[■□□] Step 1 of 3 · Preliminary quick results
[■■□] Step 2 of 3 · Deeper research
[■■■] Step 3 of 3 · Full deep research results

Start connecting Nimble right away, but do not wait on it.

Connect Nimble

If Nimble tools are listed in this session, call nimble_agents_list. Data back means the user is connected. Say nothing and go on.

If not, ask the user to connect Nimble, in one line on why: "Nimble runs the full research on live sources, with a source for every field. Connecting takes one approval, and new accounts start with a free trial." Then follow https://docs.nimbleway.com/agent-onboarding.md. Do the setup yourself and involve the user only for the approval. Never ask the user to paste an API key into the chat.

Get the inputs

InputRequiredAsk forIf skipped
AccountsyesNames and domains, or a list-
SincenoA date in YYYY-MM-DD30 days ago
Signal typesnoFor example "only exec hires and funding"all
  • Take anything the user already said. Ask only for what is missing.
  • If your host has a form or multiple-choice question tool, use it, with the required inputs first and the optional ones marked optional. Otherwise ask in one short message.
  • Do not hold up the run for optional inputs. Use the "If skipped" value.
  • Do not ask about effort. Use it only if the user brings it up.

Build the agent input from this pattern:

Check <Company> (<domain>) for changes since <YYYY-MM-DD>

Example: Check Mercury (mercury.com) for changes since 2026-09-21

  • One account per run. For a list, one run per account in parallel.
  • Always pass an explicit date in YYYY-MM-DD form.
  • If they only care about some signal types, add one line to the input.

Start both agent runs

As soon as Nimble is connected and you have the required inputs, start the agent runs before anything else, so they work while you do step 1:

  1. Create the agent from the template: nimble_agents_create(template="account-signals", agent_name="account-signals"). A 409 "already exists" means it was created before, so go on. If the template is not found, tell the user it is unavailable and stop. Do not substitute another template.
  2. Start two runs on the same input: nimble_agents_run(agent_name="account-signals", input="<the input>", effort="medium") and the same with effort="high". Leave schema and skill to the template. If the user chose an effort, start one run at that effort and number the steps 1 of 2 and 2 of 2.
  3. Tell the user once, in one line, what is running: "Running a quick search now, a deeper Nimble run (2-4 min) and a full one (5-15 min). This uses 2 agent runs."

Step 1 of 3 · Preliminary quick results

Tell them which signals usually mean a buying moment for what they sell, and anything you can find that happened at those accounts. Use a few quick searches, not the agents: nimble_search if Nimble is connected, otherwise your own web search tool. Keep it under a minute and short. Link every fact, and mark anything from memory with your knowledge cutoff.

End with one line on what is coming next. If Nimble is still not connected, say the deeper steps start once it is, and offer the connect step again.

Step 2 of 3 · Deeper research

Poll both runs with nimble_agents_run_status every 20-30 seconds. When the medium run finishes, get nimble_agents_run_result and show it:

  • A short table or brief, not raw JSON. Lead with the 2-3 most useful facts, each with its source link.
  • Point out what is new or different from step 1.
  • Say what is missing (empty fields, missing_fields, empty lists).
  • End with one line: the full run is still going and about how long it has left.

Step 3 of 3 · Full deep research results

When the high run finishes, show its result the same way. Lead with what it added or corrected compared with step 2, then the full result. This is the answer the user keeps.

If a run finishes with no output and no sources, retry it once. Do not retry a run that returned data. If the medium run fails, or the high run finishes first, go straight to step 3 and do not show the medium result after it.

Next steps

Offer, one line each, what fits:

  • Run it on a list. One run per record in parallel. See Running at scale.
  • Schedule it. Use the host's scheduler or a cron job, and pass the last run date as the new since date where the input has one.
  • Use it from code. The agent is saved as account-signals. Give a short Python or TypeScript snippet that runs it by name.

Using Nimble well

Read the page you need, when you need it: writing the task, sources, effort and cost, evaluating results, running at scale, common mistakes.

Pitfalls

  • Events on the since date itself can slip in. Keep only events strictly after it.
  • For repeat checks, keep the sources you already showed and drop them next time.

Rules

  • Never invent values. Show missing fields as missing.
  • Never print or log an API key.

Frequently asked questions

What does the Account Signals AI skill do?

Lists what changed at an account since a date: funding, exec moves, launches, pricing changes and hiring pushes, each dated and cited, using the Nimble `account-signals` agent template on live web data. Use when the user says "what changed at", "buying signals", "track my accounts", "any news on my accounts since", "trigger events", "signals for", or arrives from a Nimble use-case page. Interviews the user for the inputs, shows quick search results first, then runs the template at medium and high effort and shows each result as it arrives. Do NOT use for a full company brief (use account-br...

Why use Account Signals on TypingMind?

Because you install it once and use it with any model. Account Signals is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Account Signals in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Nimbleway/agent-skills/tree/main/skills/account-signals. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Account Signals?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Account Signals?

As many as you like. As long as a model supports skills, you can use Account Signals with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Account Signals AI skill free?

Yes. It is published on GitHub by Nimbleway under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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