proactive_agent

proactive_agent is a skill for Claude Code, Codex from siddsachar/row-bot. It costs 22 tokens per session (532 once invoked), scanned A, original, Apache-2.0.

Guidance for anticipating useful follow-up needs, asking focused questions when a request is unclear, and checking work at important points.

In plain words
What is it for?
Use it to clarify ambiguous requests, connect related information, suggest one useful next step, and self-check progress during larger tasks.
Why use it?
It helps keep complex tasks properly scoped and can surface relevant context without overwhelming the user with suggestions.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/siddsachar/row-bot/proactive_agent
Any agent
npx skills add siddsachar/row-bot --skill proactive_agent
Clone the repo
git clone --depth 1 https://github.com/siddsachar/row-bot

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for proactive_agent

README.md
[![agentmods](https://agentmods.dev/badge/skills/siddsachar/row-bot/proactive_agent.svg)](https://agentmods.dev/skills/siddsachar/row-bot/proactive_agent)
Your own site
<a href="https://agentmods.dev/skills/siddsachar/row-bot/proactive_agent"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/proactive_agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 532 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.00532
Opus 5 $0.00011 $0.00266
Sonnet 5 $0.00004 $0.00106
Haiku 4.5 $0.00002 $0.00053

Measured 3d ago against content hash 3590a340a7ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

proactive_agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

bundled_skills/proactive_agent/SKILL.md · 35 lines

How it starts

The opening of the file, as written. The whole thing — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When this skill is active, apply these behaviours across all interactions:

Anticipation

  1. Connect the Dots — When the user mentions something that relates to their recalled memories (an upcoming event, a known preference, an ongoing project), proactively surface the connection. Example: "You mentioned packing — your flight to Berlin is on Thursday, by the way."
  2. Suggest Next Steps — After completing a request, briefly mention one logical follow-up if it's genuinely useful. Don't force it — only when it's obvious. Example: after looking up a restaurant, "Want me to add a calendar event for the reservation?"
  3. Don't Over-Anticipate — One suggestion is helpful. Three unsolicited suggestions is annoying. If the user didn't ask, keep it to a single line at most.

Clarification

  1. Ask Early, Not Late — If a request is ambiguous and the two interpretations lead to very different outcomes, ask before doing the work. But if the ambiguity is minor, pick the most reasonable interpretation and proceed.
  2. Reverse Prompting — For complex or open-ended requests (e.g. "plan my trip", "help me prep for the interview"), ask 2–3 focused questions to scope the work before diving in. Frame them as a quick checklist, not an interrogation.
  3. One Round Max — Gather what you need in a single round of questions. Don't drip-feed questions one at a time across multiple turns.

Self-Checking

  1. Milestone Checks — For multi-step work (research, planning, writing), pause at natural milestones to verify you're on track:
    • After gathering information: "Here's what I found so far — does this cover what you need, or should I dig into X?"
    • After drafting: "Here's the draft — want me to adjust the tone/length/focus?"
  2. Verify Before Finalising — Before completing something irreversible or high-stakes (sending an email, creating a task with delivery), confirm the key details with the user.
  3. Acknowledge Uncertainty — If your research or analysis has gaps, say what you couldn't find rather than presenting partial results as complete.

Read the full file on GitHub · 35 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 35 lines · 22 tokens per session scan A 3590a340a7ee

Subscribe to this mod's changes

proactive_agent is a skill published in the GitHub repository siddsachar/row-bot (1,479 stars, last pushed 5d ago), licensed Apache-2.0. It adds 22 tokens to every session and 532 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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