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Dd Logs

OrganizationPopular
DataDog
dd-logs

Log management - search, pipelines, archives, and cost control.

Overview

PublisherDataDog
Repositorypup
Skill namedd-logs
Stars
1K
Forks
127
Bundled files
Instructions only
LicenseApache-2.0
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 DataDog on GitHub. Read the source before you install it.

Installation

Install the Dd Logs 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/DataDog/pup/tree/main/skills/dd-logs
  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/DataDog/pup.git /tmp/pup
mkdir -p .claude/skills
cp -r /tmp/pup/skills/dd-logs .claude/skills/dd-logs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dd Logs 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 Dd Logs 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 Dd Logs 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.

Datadog Logs

Search, process, and archive logs with cost awareness.

Prerequisites

Datadog Pup (dd-pup/pup) should already be installed:

bash
cargo install --git https://github.com/DataDog/pup

Quick Start

bash
pup auth login

Search Logs

bash
# Basic search
pup logs search --query="status:error" --from="1h"

# With filters
pup logs search --query="service:api status:error" --from="1h" --limit 100

# JSON output is the default
pup logs search --query="@http.status_code:>=500" --from="1h"

Search Syntax

QueryMeaning
errorFull-text search
status:errorTag equals
@http.status_code:500Attribute equals
@http.status_code:>=400Numeric range
service:api AND env:prodBoolean
@message:*timeout*Wildcard

Trace IDs in Log Results

Logs that show a linked trace in the Datadog UI may not include dd.trace_id / dd.span_id in API results. When a trace ID attribute is remapped for trace correlation (via JSON preprocessing or a Trace Remapper processor), the source attribute is removed and the value is stored as an internal attribute that the Logs Search API does not return. The UI's "trace" link reads that internal attribute, so UI and API results differ.

This is expected Datadog Log Management behavior, not a pup bug or an instrumentation problem. Do not retry queries or change instrumentation to "fix" it. Datadog is tracking making these values queryable (support reference FRLOGSS-4306).

Workarounds until then:

  • Emit the trace ID under a separate attribute that is not remapped (e.g. @custom.trace_id) and query that.
  • Pivot the other way: search spans by the log's service/time window via pup traces search, or use the trace link in the Datadog UI.

Pipelines

Process logs before indexing:

bash
# List pipelines
pup obs-pipelines list

# Create pipeline (JSON)
pup obs-pipelines create --file pipeline.json

Common Processors

json
{
  "name": "API Logs",
  "filter": {"query": "service:api"},
  "processors": [
    {
      "type": "grok-parser",
      "name": "Parse nginx",
      "source": "message",
      "grok": {"match_rules": "%{IPORHOST:client_ip} %{DATA:method} %{DATA:path} %{NUMBER:status}"}
    },
    {
      "type": "status-remapper",
      "name": "Set severity",
      "sources": ["level", "severity"]
    },
    {
      "type": "attribute-remapper",
      "name": "Remap user_id",
      "sources": ["user_id"],
      "target": "usr.id"
    }
  ]
}

⚠️ Exclusion Filters (Cost Control)

Index only what matters:

json
{
  "name": "Drop debug logs",
  "filter": {"query": "status:debug"},
  "is_enabled": true
}

High-Volume Exclusions

bash
# Find noisiest log sources
pup logs search --query="*" --from="1h" | jq 'group_by(.service) | map({service: .[0].service, count: length}) | sort_by(-.count)[:10]'
ExcludeQuery
Health checks@http.url:"/health" OR @http.url:"/ready"
Debug logsstatus:debug
Static assets@http.url:*.css OR @http.url:*.js
Heartbeats@message:*heartbeat*

Archives

Store logs cheaply for compliance:

bash
# List archives
pup logs archives list

# Archive config (S3 example)
{
  "name": "compliance-archive",
  "query": "*",
  "destination": {
    "type": "s3",
    "bucket": "my-logs-archive",
    "path": "/datadog"
  },
  "rehydration_tags": ["team:platform"]
}

Log-Based Metrics

Inspect log-based metrics:

bash
# List existing log-based metrics
pup logs metrics list

⚠️ Cardinality warning: Group by bounded values only.

Sensitive Data

Scrubbing Rules

json
{
  "type": "hash-remapper",
  "name": "Hash emails",
  "sources": ["email", "@user.email"]
}

Never Log

python
# In your app - sanitize before sending
import re

def sanitize_log(message: str) -> str:
    # Remove credit cards
    message = re.sub(r'\b\d{4}[-\s]?\d{4}[-\s]?\d{4}[-\s]?\d{4}\b', '[REDACTED]', message)
    # Remove SSNs
    message = re.sub(r'\b\d{3}-\d{2}-\d{4}\b', '[REDACTED]', message)
    return message

Troubleshooting

ProblemFix
Logs not appearingCheck agent, pipeline filters
High costsAdd exclusion filters
Search slowNarrow time range, use indexes
Missing attributesCheck grok parser
dd.trace_id missing but UI shows a traceExpected: remapped trace IDs become internal attributes (see Trace IDs in Log Results)

References/Documentation

Frequently asked questions

What does the Dd Logs AI skill do?

Log management - search, pipelines, archives, and cost control.

Why use Dd Logs on TypingMind?

Because you install it once and use it with any model. Dd Logs 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 Dd Logs in TypingMind?

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

Which AI models can use Dd Logs?

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 Dd Logs?

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

Is the Dd Logs AI skill free?

Yes. It is published on GitHub by DataDog under the Apache-2.0 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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