adding-capabilities

A guide for adding optional features to an existing software agent, such as pausing conversations, requesting human approval, choosing service providers, limiting tools, and searching documents.

In plain words
What is it for?
Use it to add multi-step conversations, approval before side effects, provider selection, per-request tool limits, or document search with R2R and Knowledge MCP.
Why use it?
It explains when each feature is needed and how to add it, so you do not have to design these agent workflows from scratch.

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/artesiana/agent2/adding-capabilities
Any agent
npx skills add Artesiana/agent2 --skill adding-capabilities
Clone the repo
git clone --depth 1 https://github.com/Artesiana/agent2

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,182 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 $0.00039 $0.01182
Opus 5 $0.00019 $0.00591
Sonnet 5 $0.00008 $0.00236
Haiku 4.5 $0.00004 $0.00118

Measured 3d ago against content hash 0c13676bd32c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

adding-capabilities 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.

.agents/skills/adding-capabilities/SKILL.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adding Capabilities to Agents

Overview

Agent2 capabilities are opt-in. Start with a simple agent (schema + tools + prompt), then add capabilities as your use case requires them.

When to Activate

  • User says "add resume", "add approval", "add knowledge", "add provider policy"
  • Agent needs multi-turn conversations
  • Agent needs human-in-the-loop before executing side effects
  • Agent needs cost-optimized provider routing
  • Agent needs per-request tool filtering

Capability Quick Reference

Capability When You Need It What It Adds
Pause/Resume Multi-turn workflows, clarification loops message_history serialization
Approval Workflow Human must approve before side effects pending_actions + execute endpoint
Provider Policy Cost control, prompt cache optimization provider_order in config
Tool Scoping Per-tenant or per-request tool filtering Tool policy in before_run()
Knowledge Search Agent needs domain documents R2R + Knowledge MCP via toolsets=

Pause/Resume

Add when: Agent needs to ask a question and wait for a human to answer before continuing.

1. Accept history in before_run

def before_run(input_data: dict) -> dict:
    if input_data.get("message_history"):
        input_data["_instructions"] = (
            "Continue the conversation. Read the human's response and proceed."
        )
    return input_data

2. Persist history in after_run

The framework auto-serializes _message_history into the response. Your host product stores it wherever it wants (Redis, Postgres, Convex, etc.) and sends it back on the next call.

3. Advertise in config

capabilities:
  - resume

Approval Workflow

Add when: Agent proposes side effects (send email, update records, make payments) that need human sign-off.

1. Return pending_actions from agent output or mock_result

def mock_result(input_data: dict) -> dict:
    return {
        "status": "needs_approval",
        "pending_actions": [
            {
                "action": "send_email",
                "params": {"to": "[email protected]", "body": "..."},
                "description": "Send follow-up email to the client.",
            }
        ],
    }

Read the full file on GitHub · 182 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 · 182 lines · 39 tokens per session scan A 0c13676bd32c

Subscribe to this mod's changes

adding-capabilities is a skill published in the GitHub repository Artesiana/agent2 (36 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 1,182 once invoked, about $0.0002 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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