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Hotpath Cloud

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pawurb
hotpath_cloud

Read hotpath Cloud performance verdicts with the `hotpath cloud` CLI and fix Rust performance regressions. Fetches the benchmark report of a commit or pull request, compares it with its baseline under the repository's regression policy and performance budgets, and lists what regressed and which budgets broke, as JSON. Use when the user wants to check a pull request's performance, wait for a CI benchmark, investigate a hotpath.rs PR comment, fix a performance regression or a broken budget, or validate a hotpath policy file.

Overview

Publisherpawurb
Repositoryhotpath-rs
Skill namehotpath_cloud
Stars
1.9K
Forks
61
Bundled files
Instructions only
LicenseMIT
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 pawurb on GitHub. Read the source before you install it.

Installation

Install the Hotpath Cloud 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/pawurb/hotpath-rs/tree/main/skills/hotpath_cloud
  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/pawurb/hotpath-rs.git /tmp/hotpath-rs
mkdir -p .claude/skills
cp -r /tmp/hotpath-rs/skills/hotpath_cloud .claude/skills/hotpath_cloud
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hotpath Cloud 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 Hotpath Cloud 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 Hotpath Cloud 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.

hotpath Cloud CLI

hotpath cloud is the command line client of hotpath.rs. CI uploads a hotpath benchmark report on every push to the default branch and every pull request. hotpath.rs compares each pull request report with its baseline (the report of the base branch), judges it under the repository's policy file and posts a comment on the pull request. The CLI returns the same judgement as JSON.

Documentation

The hotpath docs are the reference for every command, flag, JSON field and policy key; this skill only holds the workflow. Every page of https://hotpath.rs is served as markdown when requested with an Accept: text/markdown header:

bash
curl -sL -H 'Accept: text/markdown' https://hotpath.rs/agents_cli

Fetch https://hotpath.rs/agents_cli before the first hotpath cloud command, and the other pages when the task reaches them, instead of relying on memory. Keep -L (some pages redirect) and the header (there are no .md URLs). A #fragment is not sent to the server: fetch the whole page and find the heading.

The site documents the latest hotpath release, which can be newer than the version the project uses. Never change the project's hotpath version because the docs show a newer one. If the docs describe something that version does not have, tell the user it needs a newer hotpath instead of working around it.

PageCovers
https://hotpath.rs/agents_cliinstall and authenticate, repos, benchmarks, report, diff (flags, JSON answer, how to read it), validate-policy, init, output and exit codes
https://hotpath.rs/regression_policythe policy file: which file a run uses, sections, keys, the pull request comment and check
https://hotpath.rs/performance_budgetsbudget rules, units, broken budgets
https://hotpath.rs/ci_integrationthe CI workflow that uploads reports, troubleshooting uploads

Setup

  1. Check the CLI: hotpath cloud --help. If it is missing or has no cloud command, install it as "Install and authenticate" describes.
  2. Check the token: hotpath cloud auth. It reads HOTPATH_API_TOKEN. If it fails with invalid_token or the variable is unset, ask the user to create a token at https://hotpath.rs/app/tokens and export it. Never ask the user to paste the token into the conversation.
  3. Find the repository (OWNER/NAME, from git remote get-url origin) and the benchmark name: hotpath cloud benchmarks --repo OWNER/NAME. The benchmark is also the HOTPATH_BENCHMARK value in the repository's .github/workflows/*.yml.

validate-policy and init need no token.

Workflow: check or fix a change

Branch on the exit code, then read the JSON ("Output and exit codes"). Do not parse the human text of the pull request comment.

  1. Push the commit. CI runs the benchmark and uploads the report, which takes as long as the benchmark job.

  2. Wait for the report. Poll until it exits 0, waiting about 30 seconds between attempts and giving up after about 30 minutes:

    bash
    hotpath cloud report --repo OWNER/NAME --benchmark NAME --commit $(git rev-parse HEAD) --no-payload

    not_found means the upload has not arrived yet. If it never arrives, check the CI run with gh run list / gh run view and the "Troubleshooting" table of https://hotpath.rs/ci_integration.

  3. Read the judgement, as the "diff" section explains it:

    bash
    hotpath cloud diff --repo OWNER/NAME --benchmark NAME --commit $(git rev-parse HEAD)
  4. Exit 0: done, report the verdict and dashboard_url to the user. Exit 1: read the regressions and broken budgets, fix the code, and repeat from step 1.

--pr N or --id ID select a report instead of --commit; --advisory and --full widen what diff lists.

Useful extracts:

bash
# Regressions with the values that crossed the bar
hotpath cloud diff ... | jq '.result.sections[]? | .rows[] | select(.outcome == "regression")
  | {name, location, cells: [.cells[] | select(.crossed) | {column, base, head, change_percent}]}'

# Broken budgets with their messages
hotpath cloud diff ... | jq '.budgets.findings[] | {entity: .entity.name, actual, limit, message}'

Fixing a regression

  • Start from location of each regressed row and the crossed cells: an allocation regression points at new or larger allocations in that function, a calls / count change at extra work, sql_per_request at an N+1 query.
  • Allocations are deterministic for a fixed workload, so an allocation change is real. Timing on shared CI runners is noisy; be careful attributing a small timing change to the code.
  • Profile locally to confirm before and after a fix: run the benchmark the CI workflow runs, with the same --features, and compare the printed hotpath report.
  • A broken budget names its rule's message, which usually says what the limit protects.

Rules

  • Never loosen the policy (hotpath/*.toml) or a budget to make a regression or a broken budget go away. Fix the code, or explain the trade-off to the user and let them decide.
  • If the user asks to change the policy, fetch https://hotpath.rs/regression_policy (and https://hotpath.rs/performance_budgets for budgets), edit hotpath/policy.toml (or hotpath/<benchmark>-policy.toml) and check it with hotpath cloud validate-policy (--benchmark NAME for a benchmark's own file) before pushing. An upload with an invalid policy is refused.
  • hotpath cloud init writes the default policy when the repository has none. It never replaces an existing file without --force; do not pass --force unless the user asks.
  • HOTPATH_API_TOKEN is a credential: never print it, echo it, log it or commit it.

Frequently asked questions

What does the Hotpath Cloud AI skill do?

Read hotpath Cloud performance verdicts with the `hotpath cloud` CLI and fix Rust performance regressions. Fetches the benchmark report of a commit or pull request, compares it with its baseline under the repository's regression policy and performance budgets, and lists what regressed and which budgets broke, as JSON. Use when the user wants to check a pull request's performance, wait for a CI benchmark, investigate a hotpath.rs PR comment, fix a performance regression or a broken budget, or validate a hotpath policy file.

Why use Hotpath Cloud on TypingMind?

Because you install it once and use it with any model. Hotpath Cloud 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 Hotpath Cloud in TypingMind?

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

Which AI models can use Hotpath Cloud?

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 Hotpath Cloud?

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

Is the Hotpath Cloud AI skill free?

Yes. It is published on GitHub by pawurb under the MIT 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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