Workflow·AI & Agents·v1.0.0

DeepEval Tracing

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI.

You say
Buy it · $35 Read it before you buy $35 Written by confident-ai · unverified publisher
Context cost
3.8k tokensestimated from the bundle, loaded when it triggers
Bundle
3 files · 15.1 kBtext throughout, nothing executable
Licence
Apache-2.0paid listing
Last change
v1.0.0
Servers it uses
Noneruns standalone

What it does

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory.

Installed, it changes the agent in these ways.

What this skill changes about the agent is not written down here yet. The listing was collected from its source, and the description is in its own SKILL.md.

Workflow

Runs a procedure end to end.

observabilitytracingagentsevals
Filed under

AI & Agents

The skill itself

This is the whole product. A skill is instructions the model reads, so there is nothing behind the listing you cannot see first — the front matter loads with every session, and the body below it loads when the skill triggers.

SKILL.md5.1 kB · 100 lines
--- name: deepeval-tracing description: > Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals. license: Apache-2.0 metadata: author: Confident AI version: "1.0.0" category: observability tags: "deepeval, tracing, observe, instrumentation, integrations, spans, confident-ai" compatibility: "Python with `pip install deepeval`. Instrumentation uses the DeepEval SDK (`deepeval.tracing`). Sending traces to Confident AI requires `deepeval login` or an exported `CONFIDENT_API_KEY`." ---
25# DeepEval Tracing
26
27Use this skill to instrument an **AI application** — an LLM app, agent, RAG
28pipeline, or chatbot — with **DeepEval's native tracing** so its execution is
29visible span by span in **Confident AI's Observatory**. The work is: pick a
30supported integration when one exists, fall back to manual @observe
31otherwise, give each span a meaningful type, and add tags and metadata.
32
33This skill stops at producing well-formed traces. Attaching evaluation metrics
34and running evals is the deepeval skill's job.
35
36## Scope: AI Applications Only
37
38Instrument only the AI parts of the system — agent loops and planning, LLM
39calls, retrieval / vector search, and tool calls. The span types (llm,
40retriever, tool, agent) describe AI components. Do not trace non-AI
41software (web servers, CRUD backends, infrastructure). If the target has no
42LLM, agent, retrieval, or tool-calling component, this skill does not apply.
43
44## When to Use vs the deepeval and deepeval-otel Skills
45
46- **This skill (deepeval-tracing)** — instrument an app with the DeepEval SDK
47 (@observe, framework integrations) so traces reach Confident AI.
48- **deepeval skill** — build pytest eval suites: datasets, metrics, traced
49 evals, deepeval test run, iteration. It runs evals *against* an app this
50 skill instrumented.
51- **deepeval-otel skill** — instrument with the vendor-neutral OpenTelemetry
52 SDK instead of the DeepEval SDK (raw OTLP, including non-Python apps).
53
54The three are complementary. If unsure between this skill and deepeval-otel:
55use this one when the app is Python and you want the DeepEval SDK; use
56deepeval-otel when you want raw OpenTelemetry or the app is not Python.
57
58## Prerequisites
59
60- An AI application in Python with pip install deepeval.
61- For traces to reach Confident AI: deepeval login, or an exported
62 CONFIDENT_API_KEY (preferred for CI and non-interactive runs).
63
64## Workflow
65
661. Confirm the target is an AI application (it has LLM calls, an agent loop,
67 retrieval, or tool calls). If it has none of these, stop — this skill does
68 not apply.
692. Detect the framework, model provider, agent SDK, and vector database in use.
703. Read references/integrations.md and the exact integration doc for what was
71 detected. Prefer a native integration over manual instrumentation.
724. If no native integration fits, instrument manually with @observe. Read
73 references/tracing.md.
745. Give each span a meaningful type (llm, retriever, tool, agent) and
75 capture inputs/outputs.
766. Add trace-level tags and metadata where they help diagnose failure patterns.
77 Never trace secrets, credentials, or raw sensitive data.
787. Confirm deepeval login or CONFIDENT_API_KEY, then verify traces appear
79 in the Confident AI Observatory.
80
81## Core Principles
82
831. Instrument AI components only — llm, retriever, tool, agent spans.
84 Never trace non-AI software.
852. Prefer a supported integration over manual @observe. Manual tracing is the
86 fallback for unsupported frameworks and app-owned wrapper boundaries.
873. Read the exact integration doc before writing tracing code.
884. Give spans meaningful types; let names default to function names unless
89 there is a strong reason to override.
905. Never trace secrets, credentials, API keys, or raw sensitive user data.
916. Producing traces is the scope. Attaching metrics and running evals belong to
92 the deepeval skill; raw OpenTelemetry export belongs to deepeval-otel.
93
94## References
95
96| Topic | File |
97| --- | --- |
98| Manual instrumentation: @observe, span types, tags, metadata | references/tracing.md |
99| Integration selection rule and framework / model / vector-DB doc index | references/integrations.md |
100
In the file
SKILL.md726 words
Files3
LicenceApache-2.0
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈330
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
3,445
on trigger
The instruction body and 2 supporting files, read only when the skill fires.
1.9%
of a 200k window
Ten skills this size would take about 19% of the window before you open a file.
050k100k150k200k context window

3.8k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

Adoption
Installsnone yet
Ratingno reviews yet

The procedure it runs

The procedure has not been published here. It is in the skill’s own SKILL.md, which its author has not sent to the marketplace yet.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

It writes no files and reaches no network. All it changes is how the model reasons and writes.

What it asks for
Writes filesno
Network accessno

Read from the allowed-tools line of this skill’s own SKILL.md. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

3 files, 15.1 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md5.1 kB
  • references/integrations.md3.8 kB
  • references/tracing.md6.2 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 3 files you can review in full before installing. The Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

$35 once
DeepEval Tracing · Apache-2.0 · confident-ai
one-time
Price$35 once
LicenceApache-2.0 — the author’s, unchanged by this purchase
Paid throughStripe, once, on the card you add at the checkout
Keeps workingfor good — the files are yours once they are on disk
Updatesevery release of 1.x through this account

You can read the whole bundle before paying — the SKILL.md above is the product, not a preview of it. What the money buys is the delivery: the folder packaged and handed to your machine by key, every update its author ships, and our support if it does not do what this listing says. The terms of use are Apache-2.0, set by the author and unchanged by buying it here.

Payment runs through Stripe, on a page like this one rather than a redirect. Once there is an account it joins the same mcprush invoice as everything else you run, so there is never a second card to enter.

Which clients pick it up on their own

A skill is a folder of text. A client with a skills folder reads it without being told; everywhere else the same text works, it is just handed to the model rather than found.

Claude Code.claude/skills/
Claude Desktop
ChatGPT
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok.grok/skills/
Zed.agents/skills/
Windsurf.windsurf/skills/
Agent SDK.claude/skills/
HTTP / API
This release
Version1.0.0
Publishedno release date on file
Price$35
Referenceconfident-ai/deepeval-tracing

Versions

v1.0.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v1.0.0
  • No earlier releases have been published to the marketplace.
Pinning

Put confident-ai/deepeval-tracing@1.0.0 in the install command to hold this exact version. Without the suffix you get whatever is current the day you install, and nothing moves under you afterwards.

Reviews

no reviews yet · no installs yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Who can post

Only accounts that have had the skill installed for fourteen days, so a review is written after living with it rather than after reading it. Publishers may reply once.

Who wrote it

CO
confident-ai

Publishes on mcprush.

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