agent-callbacks

agent-callbacks is a skill for Claude Code, Codex from NicolaiLassen/orxhestra. It costs 28 tokens per session (627 once invoked), scanned A, original, Apache-2.0.

A set of callback hooks for orxhestra agents, a Python framework for building software agents. The hooks run before or after model and tool calls and can handle model errors.

In plain words
What is it for?
Use them to log requests, responses, available tools, tool calls, and model errors.
Why use it?
They make it possible to observe agent activity and respond to failures without adding logging and error code throughout the agent.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use them to log requests, responses, available tools, tool calls, and model errors.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nicolailassen/orxhestra/agent-callbacks
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.

Any agent
npx skills add NicolaiLassen/orxhestra --skill agent-callbacks
Clone the repo
git clone --depth 1 https://github.com/NicolaiLassen/orxhestra

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 agent-callbacks

README.md
[![agentmods](https://agentmods.dev/badge/skills/nicolailassen/orxhestra/agent-callbacks/github.svg)](https://agentmods.dev/skills/nicolailassen/orxhestra/agent-callbacks)
Your own site
<a href="https://agentmods.dev/skills/nicolailassen/orxhestra/agent-callbacks"><img src="https://agentmods.dev/badge/skills/nicolailassen/orxhestra/agent-callbacks/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-callbacks

Your own site · 80×15
<a href="https://agentmods.dev/skills/nicolailassen/orxhestra/agent-callbacks"><img src="https://agentmods.dev/badge/skills/nicolailassen/orxhestra/agent-callbacks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 627 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00028 $0.00627
Opus 5 $0.00014 $0.00313
Sonnet 5 $0.00006 $0.00125
Haiku 4.5 $0.00003 $0.00063

Measured 10d ago against content hash 2359a2858aa4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

agent-callbacks 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 10d 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.

docs/skills/agent-callbacks/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Callbacks

LlmAgent supports before/after hooks at the model and tool level.

Model callbacks

from orxhestra import LlmAgent, Context
from orxhestra.models.llm_request import LlmRequest
from orxhestra.models.llm_response import LlmResponse

async def log_before_model(ctx: Context, request: LlmRequest) -> None:
    print(f"Calling LLM with {len(request.messages)} messages")
    print(f"Tools available: {[t.name for t in request.tools]}")

async def log_after_model(ctx: Context, response: LlmResponse) -> None:
    print(f"LLM responded: {response.text[:100]}")
    if response.has_tool_calls:
        print(f"Tool calls: {[tc['name'] for tc in response.tool_calls]}")

async def handle_error(
    ctx: Context, request: LlmRequest, error: Exception
) -> LlmResponse | None:
    print(f"LLM error: {error}")
    return None  # push error event; or return LlmResponse to recover

agent = LlmAgent(
    name="monitored",
    model=model,
    before_model_callback=log_before_model,
    after_model_callback=log_after_model,
    on_model_error_callback=handle_error,
)

Tool callbacks

from typing import Any

async def log_tool_start(ctx: Context, tool_name: str, tool_args: dict) -> None:
    print(f"Calling tool: {tool_name}({tool_args})")

async def log_tool_end(ctx: Context, tool_name: str, result: Any) -> None:
    print(f"Tool {tool_name} returned: {str(result)[:100]}")

agent = LlmAgent(
    name="tracked",
    model=model,
    tools=[search],
    before_tool_callback=log_tool_start,
    after_tool_callback=log_tool_end,
)

AgentTool callbacks

Intercept events from child agents when using AgentTool.

from orxhestra.tools import AgentTool

def before_agent(ctx, agent):
    print(f"Delegating to sub-agent: {agent.name}")

def after_agent(ctx, agent, events):
    print(f"Sub-agent {agent.name} produced {len(events)} events")

tool = AgentTool(
    agent=researcher,
    before_agent_callback=before_agent,
    after_agent_callback=after_agent,
)

Read the full file on GitHub · 96 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. 10d ago First seen · 96 lines · 28 tokens per session scan A 2359a2858aa4

Subscribe to this mod's changes

agent-callbacks is a skill published in the GitHub repository NicolaiLassen/orxhestra (21 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 627 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.

Related

Other skills, from other repositories

ampersend

Give an agent a way to pay for things on the internet. Use when the user wants the agent to be able to pay for things online, when an HTTP call returns 402 Payment Required, when calling an endpoint that charges per request, when the user names a capability they want without a specific URL in mind, or when the user is…

edgeandnode/ampersend-sdk · 80 tokens

unit-converter

Converts values between metric and imperial units, using the project's agreed factors.

polymind-inc/agent-framework-js · 19 tokens

agent-framework-py-release

Use when cutting a Python release for the microsoft/agent-framework monorepo. Triggers on "bump py versions", "cut a python release", "prepare release PR for python", "release py packages", "bump python to X.Y.Z", or similar requests to bump Python package versions and prepare a release PR. Handles all four lifecycle…

microsoft/agent-framework · 103 tokens

foundry-hosted-agent-validation

Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.

microsoft/agent-framework · 82 tokens

build-and-test

How to build and test .NET projects in the Agent Framework repository. Use this when verifying or testing changes.

microsoft/agent-framework · 26 tokens

python-feature-lifecycle

Guidance for package and feature lifecycle in the Agent Framework Python codebase, including stage meanings, feature-stage decorators, feature enums, and how to move APIs from one stage to the next.

microsoft/agent-framework · 43 tokens