docs: surface the Marketplace listing, trim a redundant badge

CLAUDE.md

@@ -200,7 +200,7 @@ make lint        # custom architectural lint rules (CE001+)
 make verify      # All of the above + coverage check (CI equivalent)
 ```
 
-When fixing a bug, ask: *could a custom lint rule have prevented this?* If the root cause is a mechanically detectable pattern (e.g., "always import from `coder_eval.models`", "never call blocking IO in async"), add a rule to `tests/lint/rules/` following the CE001+ pattern and wire it up in `tests/lint/runner.py`. This turns a one-time fix into permanent enforcement. See `tests/test_custom_lint.py` for how rules are tested. (Doc-surface / whole-tree rules that reason over Markdown/YAML or the entire `src/` tree rather than one `.py` AST at a time — CE027–CE031 — are not `BaseRule`s in the runner; they are wired as dedicated `@pytest.mark.lint` test classes. CE031 guards against dead config: a behavior-driving field on `SimulationConfig`/`RunLimits`/`Dataset` that no code reads by name.)
+When fixing a bug, ask: *could a custom lint rule have prevented this?* If the root cause is a mechanically detectable pattern (e.g., "always import from `coder_eval.models`", "never call blocking IO in async"), add a rule to `tests/lint/rules/` following the CE001+ pattern and wire it up in `tests/lint/runner.py`. This turns a one-time fix into permanent enforcement. See `tests/test_custom_lint.py` for how rules are tested. (Doc-surface / whole-tree rules that reason over Markdown/YAML or the entire `src/` tree rather than one `.py` AST at a time — CE026–CE031 — are not `BaseRule`s in the runner; they are wired as dedicated `@pytest.mark.lint` test classes. CE031 guards against dead config: a behavior-driving field on `SimulationConfig`/`RunLimits`/`Dataset` that no code reads by name. CE026 keeps the GitHub Action's three onboarding surfaces honest: a page's *first* Action snippet must show the agent-runtime prerequisite steps (pinned to the `action-dogfood` job that proves them in CI), a zero-install absolute next to such a snippet must name the channel it means, and every `github.com/marketplace/actions/<slug>` link plus the shields badge label must match `action.yml`'s `name:`.)
 
 Adding a user-facing field to one of the models CE030 tracks (`TaskDefinition`, `RunLimits`, `Dataset`, `SimulationConfig` — see `tests/lint/doc_schema_parity.py`) means documenting it in its guide (mention the field name as inline code) or adding an `EXEMPT` entry with a reason it is not user-authored. `make lint` fails otherwise.
 

README.md

@@ -1,8 +1,8 @@
 # Coder Eval — evaluate & benchmark AI coding agents and Claude Code skills
 
 [![PyPI](https://img.shields.io/pypi/v/coder-eval.svg)](https://pypi.org/project/coder-eval/)
+[![GitHub Marketplace](https://img.shields.io/badge/marketplace-coder__eval-2ea44f.svg)](https://github.com/marketplace/actions/coder_eval)
 [![Website](https://img.shields.io/badge/website-coder--eval.com-1f6feb.svg)](https://coder-eval.com)
-[![Docs](https://img.shields.io/badge/docs-coder--eval.com%2Fdocs-1f6feb.svg)](https://coder-eval.com/docs)
 [![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE)
 [![Python 3.13+](https://img.shields.io/badge/python-3.13%2B-blue.svg)](https://www.python.org/downloads/)
 [![CI](https://github.com/UiPath/coder_eval/actions/workflows/pr-checks.yml/badge.svg)](https://github.com/UiPath/coder_eval/actions/workflows/pr-checks.yml)
@@ -97,12 +97,18 @@ the full setup.
 
 ## Use as a GitHub Action
 
-A composite action at the repo root runs `coder-eval` as a CI gate — it installs
-the pinned CLI, runs your tasks, writes a JUnit XML report, appends `run.md` to
-the job summary, and fails the step on any task/gate failure:
+A composite action — on the Marketplace as
+[**coder_eval**](https://github.com/marketplace/actions/coder_eval) — runs
+`coder-eval` as a CI gate. It installs the pinned CLI, runs your tasks, writes a
+JUnit XML report, appends `run.md` to the job summary, and fails the step on any
+task/gate failure:
 
 ```yaml
-- uses: UiPath/coder_eval@v0    # becomes @v1 once 1.0.0 ships; @vX.Y.Z pins exactly
+- uses: actions/setup-node@v4      # the claude-code agent needs the Claude CLI…
+  with: { node-version: '20' }
+- run: npm install -g @anthropic-ai/claude-code
+
+- uses: UiPath/coder_eval@v0       # …then run the gate (@v1 once 1.0.0 ships; @vX.Y.Z pins exactly)
   with:
     tasks: tests/tasks/**/*.yaml
     model: claude-sonnet-5
@@ -154,9 +160,11 @@ code: the step fails if *either* coder-eval exits non-zero *or* any task's
 alone.
 
 > **Agent runtime is the caller's responsibility.** The action is agent-agnostic —
-> it installs `coder-eval` but no coding-agent runtime. Tasks using the default
-> `claude-code` agent need the `claude` CLI on `PATH` (`actions/setup-node` +
-> `npm install -g @anthropic-ai/claude-code`) in the job before the action runs.
+> it installs `coder-eval` but no coding-agent runtime, which is why the example
+> above starts with `actions/setup-node` +
+> `npm install -g @anthropic-ai/claude-code`: the default `claude-code` agent
+> needs the `claude` CLI on `PATH` before the action runs. Swap those steps for
+> your own agent's runtime as needed.
 
 > **Security.** Evaluated tasks execute agent-generated code. Do **not** run this
 > action under `pull_request_target` with secrets exposed to untrusted fork PRs —
@@ -188,7 +196,7 @@ alone.
 | [Bring Your Own Dataset](docs/DATASETS.md) | Fan a single task out over a dataset |
 | [Dialog Mode](docs/DIALOG_MODE.md) | Evaluate agents in multi-turn conversation via a simulated user |
 | [Docker Isolation](docs/DOCKER_ISOLATION.md) | The container sandbox driver, with custom images |
-| [CI Gate & GitHub Action](docs/CI_GATE.md) | Run Coder Eval as a CI gate — the packaged Action, JUnit output, score floor |
+| [CI Gate & GitHub Action](docs/CI_GATE.md) | Run Coder Eval as a CI gate — the Marketplace Action, JUnit output, score floor |
 | [Extending Coder Eval](docs/EXTENDING.md) | Author a custom agent, criterion, or model pricing via the plugin SPI |
 | [Report Schema](docs/REPORT_SCHEMA.md) | Field-level reference for run.json / variant.json / task.json |
 | [How It Compares](docs/comparison.md) | vs. SWE-bench, SkillsBench, Harbor, OpenAI Evals, hand-rolled scripts |

docs/CI_GATE.md

@@ -1,36 +1,46 @@
 ---
 description: >-
-  Run Coder Eval as a CI gate — the packaged composite GitHub Action, JUnit XML
-  output for test-report ingestion, and an optional per-task score floor.
+  Run Coder Eval as a CI gate — the coder_eval GitHub Action from the Actions
+  Marketplace, JUnit XML output for test-report ingestion, and an optional
+  per-task score floor.
 ---
 
 # CI Gate: GitHub Action & JUnit reports
 
-Coder Eval ships a **packaged CI gate**: a composite GitHub Action that installs
-the CLI, runs your tasks, emits a JUnit XML report, appends the run summary to the
-job summary, and fails the build on any task/gate failure. This page is the
-reference for the Action and the JUnit output. For a step-by-step walkthrough
+Coder Eval ships a **packaged CI gate**: a composite GitHub Action — on the
+Actions Marketplace as
+[**coder_eval**](https://github.com/marketplace/actions/coder_eval) — that
+installs the CLI, runs your tasks, emits a JUnit XML report, appends the run
+summary to the job summary, and fails the build on any task/gate failure. This
+page is the reference for the Action and the JUnit output. For a walkthrough
 (including a hand-rolled workflow), see
 [Tutorial 02 — Running Coder Eval in CI](tutorials/02-ci-pipeline.md).
 
 ## The GitHub Action
 
-A composite action lives at the repo root (`action.yml`), so you can reference it
-directly:
+The action is published on the GitHub Actions Marketplace as
+[**coder_eval**](https://github.com/marketplace/actions/coder_eval). It is a
+composite action living at the repo root (`action.yml`), so you reference it by
+repo path — there is no Marketplace install step:
 
 ```yaml
-- uses: UiPath/coder_eval@v0    # becomes @v1 once 1.0.0 ships; @vX.Y.Z pins exactly
+- uses: actions/setup-node@v4      # the claude-code agent needs the Claude CLI…
+  with: { node-version: '20' }
+- run: npm install -g @anthropic-ai/claude-code
+
+- uses: UiPath/coder_eval@v0       # …then run the gate (@v1 once 1.0.0 ships; @vX.Y.Z pins exactly)
   with:
     tasks: tests/tasks/**/*.yaml
     model: claude-sonnet-5
     env: |
       ANTHROPIC_API_KEY=${{ secrets.ANTHROPIC_API_KEY }}
 ```
 
-The action is **agent-agnostic** — it installs `coder-eval` but *not* any
-coding-agent runtime. Tasks using the default `claude-code` agent need the
-`claude` CLI on `PATH` (Node + `@anthropic-ai/claude-code`), provided by your job
-*before* this step runs.
+The first two steps are there because the action is **agent-agnostic** — it
+installs `coder-eval` but *not* any coding-agent runtime. Tasks using the default
+`claude-code` agent need the `claude` CLI on `PATH` (Node +
+`@anthropic-ai/claude-code`), provided by your job *before* the action runs; swap
+those steps for your own agent's runtime as needed.
 
 ### Inputs
 

docs/index.md

@@ -85,7 +85,7 @@ New here? Start with **[Tutorial 01 — Your First Evaluation](tutorials/01-firs
 | [Bring Your Own Dataset](DATASETS.md) | Fan a single task out over a dataset |
 | [Dialog Mode](DIALOG_MODE.md) | Evaluate agents in multi-turn conversation via a simulated user |
 | [Docker Isolation](DOCKER_ISOLATION.md) | The container sandbox driver, with custom images |
-| [CI Gate & GitHub Action](CI_GATE.md) | Run Coder Eval as a CI gate — the packaged Action, JUnit output, score floor |
+| [CI Gate & GitHub Action](CI_GATE.md) | Run Coder Eval as a CI gate — the Marketplace Action, JUnit output, score floor |
 | [Extending Coder Eval](EXTENDING.md) | Author a custom agent, criterion, or model pricing via the plugin SPI |
 | [Report Schema](REPORT_SCHEMA.md) | Field-level reference for run.json / variant.json / task.json |
 | [How It Compares](comparison.md) | vs. SWE-bench, SkillsBench, Harbor, OpenAI Evals, hand-rolled scripts |

docs/llms.txt

@@ -32,7 +32,7 @@ and A/B plumbing.
 - [Bring Your Own Dataset](https://coder-eval.com/docs/datasets): Fan a single task out over a dataset
 - [Dialog Mode](https://coder-eval.com/docs/dialog-mode): Evaluate agents in multi-turn conversation via a simulated user
 - [Docker Isolation](https://coder-eval.com/docs/docker-isolation): The container sandbox driver, with custom images
-- [CI Gate & GitHub Action](https://coder-eval.com/docs/ci-gate): Run Coder Eval as a CI gate — the packaged Action, JUnit output, score floor
+- [CI Gate & GitHub Action](https://coder-eval.com/docs/ci-gate): Run Coder Eval as a CI gate — the Marketplace Action, JUnit output, score floor
 - [Extending Coder Eval](https://coder-eval.com/docs/extending): Author a custom agent, criterion, or model pricing via the plugin SPI
 - [Report Schema](https://coder-eval.com/docs/report-schema): Field-level reference for run.json / variant.json / task.json
 - [How It Compares](https://coder-eval.com/docs/comparison): vs. SWE-bench, SkillsBench, Harbor, OpenAI Evals, hand-rolled scripts

docs/tutorials/02-ci-pipeline.md

@@ -161,8 +161,10 @@ jobs:
 ## Shortcut: the packaged action
 
 The five steps above spell out the mechanics, but Coder Eval also ships a
-composite action at the repo root that bundles install + run + JUnit report +
-job-summary + fail-on-failure into one step:
+composite action — on the Marketplace as
+[**coder_eval**](https://github.com/marketplace/actions/coder_eval) — that
+bundles install + run + JUnit report + job-summary + fail-on-failure into one
+step:
 
 ```yaml
       - uses: actions/setup-node@v4      # the claude-code agent needs the Claude CLI…

mkdocs.yml

@@ -87,7 +87,7 @@ extra:
     DATASETS.md: "Fan a single task out over a dataset"
     DIALOG_MODE.md: "Evaluate agents in multi-turn conversation via a simulated user"
     DOCKER_ISOLATION.md: "The container sandbox driver, with custom images"
-    CI_GATE.md: "Run Coder Eval as a CI gate — the packaged Action, JUnit output, score floor"
+    CI_GATE.md: "Run Coder Eval as a CI gate — the Marketplace Action, JUnit output, score floor"
     EXTENDING.md: "Author a custom agent, criterion, or model pricing via the plugin SPI"
     REPORT_SCHEMA.md: "Field-level reference for run.json / variant.json / task.json"
     comparison.md: "vs. SWE-bench, SkillsBench, Harbor, OpenAI Evals, hand-rolled scripts"