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Give Me Tips

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code-yeongyu
give-me-tips

Explains any senpi tip in depth, including Tip: lines in the TUI. Use when the user asks about a tip, what a tipped feature does, or which tips they can see.

Overview

Publishercode-yeongyu
Repositoryoh-my-openagent
Skill namegive-me-tips
Stars
69.1K
Forks
5.7K
Bundled files
Instructions only
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 code-yeongyu on GitHub. Read the source before you install it.

Installation

Install the Give Me Tips 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.
  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/code-yeongyu/oh-my-openagent.git /tmp/oh-my-openagent
mkdir -p .claude/skills
cp -r /tmp/oh-my-openagent/packages/omo-senpi/skills/give-me-tips .claude/skills/give-me-tips
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Give Me Tips 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 Give Me Tips 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 Give Me Tips 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.

give-me-tips - explain any senpi tip, in depth

Purpose

Senpi shows the user tips: startup tips, working tips, and Tip: lines injected by omo components. When the user asks about any of them - "what was that Tip: line", "what does this tip mean", "how does that feature work" - this skill produces a DEEP explanation of that exact tip, in the USER'S language (match the language they asked in, always).

Specific over generic, every time. "It retries on failure" is a failure of this skill. "It detects the refusal from the stopDetails on the assistant message_end event, gates on the architect category in your .omo/omo.json, and only then injects the directive" is the bar. The user asked because the tip made them curious; reward that curiosity with the real mechanism, not a summary of the tip text they already read.

Query the live tip list FIRST

Never explain from memory. Get the ground truth of what tips exist:

  1. Run senpi --list-tips. It prints JSON: [{id, text, requiresCommand?}]. Match the user's tip against this list by id or by text fragment.
  2. If the flag is unavailable on this senpi version, fall back to reading the catalog sources directly at packages/coding-agent/src/modes/interactive/tips/catalog/ inside the installed @code-yeongyu/senpi package (find it via the senpi install path or node_modules) or in a local clone of code-yeongyu/senpi.

Then - and this is the part most explanations get wrong - available tips DIFFER per user. The catalog is the superset; what THIS user can actually see is gated by:

  • the tips toggle in the senpi agent dir settings.json (tips can be off entirely),
  • tipsHistory in that same settings/state, which drives cooldown rotation so a tip the user saw recently will not reappear for a while,
  • requiresCommand gating: a tip tied to a command only shows when that command is available,
  • keybinding availability: some tips reference bindings the user's setup may not have.

Read the senpi agent dir settings.json (and its tips history state) BEFORE explaining, and tell the user which tips they personally can encounter and why - not the full catalog as if everyone sees everything.

Verify before explaining

Never invent behavior. A tip is a one-line promise; the truth lives in code. Before writing the explanation, read the actual feature implementation:

  • senpi itself: code-yeongyu/senpi, under packages/coding-agent/ (the tips catalog lives at packages/coding-agent/src/modes/interactive/tips/catalog/; the features the tips point at live in the surrounding packages),
  • omo components: code-yeongyu/oh-my-openagent, under packages/omo-senpi/.

Cite the concrete file paths you read in your explanation. If the code and the tip text disagree, the code wins - say so and show what it actually does.

Tone: BRAG

These tips exist because someone engineered something genuinely impressive, and a flat doc summary betrays that. Lead with the most impressive engineering behind the tip - the clever detection, the race that had to be closed, the state machine hiding under one sentence - and showcase it. The user should finish the explanation feeling like they got a tour of the engine room, not a sticker reading. Concrete mechanics over adjectives: name the events, the gates, the file paths, the exact order of operations.

The Fable-5-refusal tip specifically

When the user asks about the tip that appears after a Fable 5 refusal ("Fable 5 refused, but its refusals should not wear you down..."), explain the full fallback-architect pipeline, citing packages/omo-senpi/src/components/fallback-architect/:

  1. Refusal detection (detection.ts): the component watches message_end events and applies the same refusal semantics senpi's own retry classifier uses - stopReason checked FIRST (so an abort or normal stop carrying stale stopDetails can never masquerade as a refusal), then stopDetails of type refusal/sensitive, plus the Anthropic usage-policy errorMessage pattern for provider-side blocks that carry no stopDetails at all.
  2. Architect category gate (architect-gate.ts): on a model_select with source "fallback" moving AWAY from claude-fable-5 with a refusal pending, the component checks the user's own omo config for an active architect category. No architect category, no nudge - the feature never pretends depth is reachable when it is not.
  3. Hidden directive (directive.ts, customType omo-fallback-architect:directive, display:false): the fallback model gets a hidden 5-step playbook - decompose the problem, consult task(category: "architect") with one self-contained query per part (the architect consultant IS Fable 5, reached through a lane its refusal cannot block), run independent consultations in parallel, and split refused queries into smaller benign sub-questions instead of resending. The directive also tells the model the user was shown the visible tip, so the two never contradict each other.
  4. Visible tip (tip-message.ts, customType omo-fallback-architect:tip, display:true): rendered as a dim Tip: block via a registered message renderer. It names the ACTUAL fallback model the session landed on, reassures the user that the refused question is still being reasoned through in essence, and notes Fable-5-grade depth stays reachable through the architect category.

The engineering worth bragging about: the refusal never deletes the user's question. Detection arms on the exact assistant message that preceded the switch (a later successful answer disarms it), reminders ride inside queued prompts instead of burning extra assistant turns, and the whole nudge self-cancels the moment Fable 5 becomes the active model again or senpi reverts the fallback. One refusal triggers a coordinated downgrade in visibility with zero downgrade in reachable reasoning depth.

The Kibitzer recollection notice specifically

When the user asks about the ✦ Kibitzer line that shows up mid-session ("recalled memory: ..."), or about the memory tip that promises stored memory can resurface on its own, explain the whole resident Kibitzer sidecar, citing packages/omo-senpi/src/components/memory/kibitzer/ and packages/memory-core/src/recall/. This is NOT the periodic save reminder: memory.nudge in nudge-wiring.ts asks the agent to WRITE memory every N user turns, while Kibitzer only READS memory and hands one hint back. Keep the two apart in the explanation.

  1. Candidate collection (recall-wiring.ts, recall-session-read.ts, recall-query-planner-tools.ts): on every prompt and tool_call the component snapshots the live session synchronously (the host disposes the ctx once the handler returns), runs a lexical planner over the user-only text window plus the last 8 tool-argument payloads, and scores memory files against it. Memory-owned hidden channels are excluded from the window, so a previous hint can never seed the next query.
  2. One resident sidecar per session (kibitzer/index.ts, kibitzer/sidecar.ts, kibitzer/events.ts): each main session owns ONE quick-category in-process child, created lazily and disposed at session shutdown. Every prompt, tool_call and tool_result reaches it as a bounded event - secrets redacted before truncation, tool args capped at 400 characters, result heads at 600, assistant text at 1500, prompts at 4000, eval.summary preferred over code, the newest 20 events kept and older ones folded into a one-line digest. Events only buffer; a model turn (a wake) happens only when the batch carries a memory path this sidecar has not judged and the session has not surfaced. An idle child is revived with a follow-up; a running turn is steered.
  3. Wake governance (kibitzer/wake-policy.ts, kibitzer/wake-slot.ts): before a wake the sidecar takes one slot of a machine-wide lease (memory-core's recall-wake lock domain, memory.recall.max_concurrent_wakes, default 2, FIFO tickets, dead-owner recovery); when every slot is busy it keeps buffering and retries at the next hook, never dropping an event. A wake is limited to memory.recall.tool_budget tool calls (default 8) and 90 seconds; hitting either ends the wake without counting as a failure, and nudges accepted before the cut are still delivered. Accepted-nudge cooldown is 2 wakes per 10 minutes per session. When the child's own context passes 60% of memory.recall.sidecar_max_tokens (default 48000) it is replaced by a fresh child seeded with the delivered paths, the rejected paths, a one-line task summary and the last cursor. A failed child is disposed and recreated after a jittered exponential backoff (1 s doubling to 5 min) with every buffered event kept.
  4. Exactly five read-only tools (kibitzer/tools/, persona at packages/memory-core/src/recall/assets/kibitzer-persona.md): read and grep inside the workspace, session_entries(since) over the parent transcript minus memory-owned hidden entries, memory with only search and read over the committed memory corpus, and nudge(path, hint). No bash, edit, write, and no tool that writes memory: the sidecar can look before it speaks, but it cannot act. Its instruction is that silence is the default: it nudges only when a stored memory would change the agent's next action (it contradicts the current approach, records a past failure of it, answers a question the agent is about to re-derive, or names a constraint being ignored). Topical similarity alone is rejected.
  5. Hint contract (kibitzer/tools/nudge.ts, kibitzer/nudge-tool.ts, packages/memory-core/src/recall/gate.ts): the path must be one the sidecar was offered this lifetime or found through its own memory search, must not already be surfaced this session, and must not be a system/ path; the hint is one factual present-tense sentence, at most 200 characters (NUDGE_HINT_MAX_CHARS), single line, and secret-like text is rejected. The parent re-validates every accepted nudge against the same rules plus memory.recall.max_items (default 2, range 1 to 5, counted per wake) before anything is persisted.
  6. Delivery (kibitzer/delivery.ts, recall-drain.ts): accepted nudges are marked surfaced in the session ledger at ACCEPT time, so a later wake can't repeat them. The model-facing half is a hidden omo-kibitzer:recall message (display: false) carrying a <recalled-memory source="[[path]]"> block that says the memory is a hint, not current state, and must be verified. It is steered in at the next tool_result when nothing else is pending, ridden in on another source's idle flush, or drained into the next prompt. A compaction of the main session drops everything delivery still holds, but never the sidecar itself - it keeps its context.
  7. The visible half (kibitzer/notice.ts): because senpi draws nothing for the hidden message, the component appends an omo-kibitzer:nudged entry and renders it as Kibitzer advice: a single fixed Kibitzer title (✦ Kibitzer, accent tone; opener-era records carry a retired opener field that is ignored) over recalled memory: <hint>, recalled memory: ... for a second nudge, and the source paths in dim text. Expanding the entry reveals the caveat that it's a hint, not current state. The record keeps via (steer, wake, or prompt) for forensics, but no provenance is ever drawn. It's a transcript entry, not a toast: nothing pops over the input, and the renderer is fail-closed, so a malformed record draws nothing rather than a half-formed notice.

What's worth bragging about: the user sees one calm line, and behind it a resident read-only judge that remembers what it already judged, five tools that can only look, a machine-wide cap on how many judges think at once, a per-wake tool budget and deadline, a 200-character hint budget, a ledger that guarantees a memory surfaces at most once per session, and a sidecar that reseeds itself before its own context runs out. A judge that finds nothing says nothing, and that silence is the designed outcome, not a failure; a failing model backs off quietly instead of spamming notices. Its audit trail is the child's own session JSONL under recall/sidecars/<encoded-session>/ - no per-run directories. Turn the whole thing off with memory.recall.enabled: false, the only off switch.

Frequently asked questions

What does the Give Me Tips AI skill do?

Explains any senpi tip in depth, including Tip: lines in the TUI. Use when the user asks about a tip, what a tipped feature does, or which tips they can see.

Why use Give Me Tips on TypingMind?

Because you install it once and use it with any model. Give Me Tips 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 Give Me Tips in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/give-me-tips. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Give Me Tips?

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 Give Me Tips?

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

Is the Give Me Tips AI skill free?

It is published on GitHub by code-yeongyu. 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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