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Advisor

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scdenney
advisor

Consults Fable as an independent, read-only reviewer at an effort the caller matches to the question. The calling session (usually Opus, or Haiku) holds the task and escalates one decision point. Use before committing to an interpretation or a substantial piece of writing or analysis, when stuck or not converging, when changing approach, or as a final check on a finished task. Fallback for when the native advisor tool is unavailable. Not for a session already running Fable.

Overview

Publisherscdenney
Repositoryopen-science-skills
Skill nameadvisor
Stars
69
Forks
3
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by scdenney on GitHub. Read the source before you install it.

Installation

Install the Advisor 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/scdenney/open-science-skills/tree/main/plugin/skills/advisor
  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/scdenney/open-science-skills.git /tmp/open-science-skills
mkdir -p .claude/skills
cp -r /tmp/open-science-skills/plugin/skills/advisor .claude/skills/advisor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Advisor 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 Advisor 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 Advisor 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.

advisor — escalate a decision point to Fable

fable-advisor.sh starts an isolated Fable session that reviews one decision point and returns. If the session has the native advisor tool (/advisor fable), use that; this skill is the fallback for when it is off or reports itself unavailable.

The two seats

SeatModelRole
MainOpus, or Haiku for cheap sustained workHolds the task, the context, and the decision. Does the work.
AdvisorFableReads one briefing, returns one review. Never edits files.

This is an escalation, not a peer review: a working model reaches up to the premier model when a decision point is worth it. The script pins the advisor to Fable and never falls back to another family, since a same-family fallback defeats the point. Inside orchestrate, an Opus lead is the main seat and the consult is one bounded call, not a delegation.

A session running Fable does not use this skill. A second, isolated Fable is the same model answering the same question. A Fable session that wants an independent read goes cross-vendor: orchestrate's Codex peer (codex-peer.sh --mode cross-check) or /model-committee. Decide from the model line Claude Code injects into the session ("You are powered by the model named …"), say so, and stop.

Choose Fable's effort

The caller picks the effort for each consult and tells the user the level and the reason in one line ("advisor at xhigh: choosing between two identification strategies"). It is never inherited from the session.

EffortUse for
high (default)a completion check; a bounded question whose answer you can check; a sanity read before writing
xhighan interpretation or design decision; stuck or non-converging work; a proposed change of approach
maxhigh-stakes and hard to verify: an identification strategy, a publication-facing claim, an irreversible choice

Anthropic recommends starting Fable 5.1 at high and stepping up to xhigh or max for the most capability-sensitive work; that is the basis for this ladder. A cheap session can still buy a max consult when the question warrants it.

Compose the briefing

The script starts a new claude process with no memory of this conversation, so the briefing carries everything: the task, what has been done, the current approach or the exact claim, and the precise question, with file paths and line numbers.

The consult runs with --safe-mode: no CLAUDE.md, skills, plugins, hooks, MCP servers, custom commands, or agents load (org-managed policy still applies). It sees the files in the -C directory and nothing else. Quote any project convention, methodological requirement, or house style the answer depends on into the briefing; asking "does this meet our reporting standard?" without stating the standard gets a confident generic answer.

When to consult

  • Before substantive work — before writing, committing to an interpretation, or building on an assumption. Orientation does not count.
  • When you believe a task is complete. Make the deliverable durable first; a consult takes real time.
  • When stuck — recurring errors, an approach that will not converge, results that do not fit.
  • When considering a change of approach.

On work longer than a few steps, consult once before the approach sets and once before declaring done. On short tasks, once or not at all.

Weigh the advice as evidence, not authority: primary sources and empirical failure outrank it. If your evidence and Fable's advice conflict, one more consult stating the conflict plainly ("I found X, you suggest Y — which constraint breaks the tie?") is cheaper than committing to the wrong branch.

Run a consult

bash
OSS_ROOT=$(ls -d ~/.claude/plugins/cache/open-science-skills/oss/*/ 2>/dev/null | sort -V | tail -1)
"${OSS_ROOT}skills/advisor/scripts/fable-advisor.sh" \
  --prompt-file <briefing-path> \
  --out <output-path> \
  --effort <high|xhigh|max> \
  -C "$PWD"

Give the Bash call timeout: 900000 as a backstop; the script has its own timeout (--timeout, default 900 s — raise it for a max consult on a large briefing). Read the output and act on it; if you diverge from it, be able to say why. The Codex plugin's "stop after presenting findings" guidance applies to code-review handoffs, not here.

Notes

  • fable-advisor.sh --check confirms the claude CLI is on PATH and reports the default effort. A hand-installed copy under ~/.claude/skills/ shadows the plugin's and drifts out of date.
  • The consult runs --permission-mode plan and --no-session-persistence: advisory only, not resumable.
  • The script clears ANTHROPIC_API_KEY, so the consult bills the subscription even if the shell exports a key.
  • The model defaults to the fable alias; --model <id> pins a version. If the alias is unavailable, report it and ask rather than substituting another family.
  • Companion: codex/advisor/ is the same pattern for a Codex session, with gpt-6-astra in the advisor seat and the same effort ladder.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Advisor AI skill do?

Consults Fable as an independent, read-only reviewer at an effort the caller matches to the question. The calling session (usually Opus, or Haiku) holds the task and escalates one decision point. Use before committing to an interpretation or a substantial piece of writing or analysis, when stuck or not converging, when changing approach, or as a final check on a finished task. Fallback for when the native advisor tool is unavailable. Not for a session already running Fable.

Why use Advisor on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/scdenney/open-science-skills/tree/main/plugin/skills/advisor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Advisor?

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 Advisor?

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

Is the Advisor AI skill free?

It is published on GitHub by scdenney. Check the repository for licensing terms. 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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