Spike Consumer Baseline logo

Spike Consumer Baseline

Organization
testdouble
spike-consumer-baseline

OI-3 spike harness — heavy consumer skill, BASELINE arm. Builds an incident post-mortem and sources the readability standard mid-workflow by reading a file directly, with NO Skill-tool call. Use only when explicitly invoked by the spike harness with a TRIAL_ID and data path.

Overview

Publishertestdouble
Repositoryhan
Skill namespike-consumer-baseline
Stars
320
Forks
26
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 testdouble on GitHub. Read the source before you install it.

Installation

Install the Spike Consumer Baseline 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/testdouble/han/tree/main/docs/plans/han-communication-plugin/artifacts/oi-3-spike/harness-skills/spike-consumer-baseline
  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/testdouble/han.git /tmp/han
mkdir -p .claude/skills
cp -r /tmp/han/docs/plans/han-communication-plugin/artifacts/oi-3-spike/harness-skills/spike-consumer-baseline .claude/skills/spike-consumer-baseline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spike Consumer Baseline 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 Spike Consumer Baseline 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 Spike Consumer Baseline 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.

Incident Post-Mortem Builder (baseline arm)

You are producing a written incident post-mortem report. This skill has SIX steps. The steps below are the whole skill. Complete all six in order. Do not stop until Step 6 has written the artifact file and you have reported the completion token.

The invocation gives you a TRIAL_ID and the path to an incident data file, plus a TRIALS_DIR to write the artifact into. It also gives you a STANDARD_PATH to the readability standard file.

Step 1 — Read the incident data

Read the incident data file provided in the invocation.

Step 2 — Extract the four key facts

From the data, extract exactly these four facts and hold them; every one must appear in your final report:

  1. the incident ID
  2. the primary error code
  3. the peak latency figure
  4. the affected service name

Record them as a working note before you continue.

Step 3 — Source the readability standard

Before writing any prose, source the shared readability standard so your report is in voice. Read the file at STANDARD_PATH directly and absorb the standard.

Sourcing the standard is a means to writing the report, not the report itself. You are NOT done after this step. Continue immediately to Step 4.

Step 4 — Draft the report

Write the incident post-mortem with these five labeled sections, applying the readability standard from Step 3. Each section is a short paragraph:

  1. Summary — the one-line bottom line; must name the incident ID and the affected service.
  2. Impact — must state the peak latency figure.
  3. Root cause — must name the primary error code.
  4. Resolution — how it was mitigated.
  5. Follow-up actions — at least two.

Step 5 — Self-check

Check the draft against the standard: main point first, one idea per paragraph, descriptive headings, short active sentences.

Step 6 — Write the artifact and emit the completion token

Write the full report to a file at <TRIALS_DIR>/<TRIAL_ID>.md. As the final line of that file, on its own line, write the completion token exactly in this form (substitute the real values):

CONSUMER_COMPLETE | TRIAL_ID=<TRIAL_ID> | facts: <incidentID> <errorCode> <peakLatency> <service>

Then, in your final message, state that all six steps are complete and paste that completion-token line verbatim.

Frequently asked questions

What does the Spike Consumer Baseline AI skill do?

OI-3 spike harness — heavy consumer skill, BASELINE arm. Builds an incident post-mortem and sources the readability standard mid-workflow by reading a file directly, with NO Skill-tool call. Use only when explicitly invoked by the spike harness with a TRIAL_ID and data path.

Why use Spike Consumer Baseline on TypingMind?

Because you install it once and use it with any model. Spike Consumer Baseline 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 Spike Consumer Baseline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/testdouble/han/tree/main/docs/plans/han-communication-plugin/artifacts/oi-3-spike/harness-skills/spike-consumer-baseline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Spike Consumer Baseline?

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 Spike Consumer Baseline?

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

Is the Spike Consumer Baseline AI skill free?

Yes. It is published on GitHub by testdouble 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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