ask

A tool for asking questions about code by finding the earlier AI conversation that led to its creation. It helps explain how code works and why it was designed that way.

In plain words
What is it for?
Use it while exploring an AI-written codebase to ask about a selected section, a file, a symbol, or a specific line range.
Why use it?
Code can be difficult to understand from the final files alone, especially when the original decisions and constraints are not documented nearby.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/git-ai-project/git-ai/ask
Any agent
npx skills add git-ai-project/git-ai --skill ask
Clone the repo
git clone --depth 1 https://github.com/git-ai-project/git-ai

Made for: Claude Code, Codex.

Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,482 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00054 $0.01482
Opus 5 $0.00027 $0.00741
Sonnet 5 $0.00011 $0.00296
Haiku 4.5 $0.00005 $0.00148

Measured 2d ago against content hash b9bb8bd00413, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ask scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ask/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ask Skill

Answer questions about AI-written code by finding the original prompts and conversations that produced it, then embodying the author agent's perspective to answer.

Main Agent's Job (you)

You do the prep work, then hand off to a fast, tightly scoped subagent:

  1. Resolve the file path and line range — check these sources in order:

    a) Editor selection context (most common). When the user has lines selected in their editor, a <system-reminder> is injected into the conversation like:

    The user selected the lines 2 to 4 from /path/to/file.rs:
    _flush_logs(args: &[String]) {
        flush::handle_flush_logs(args);
    }
    

    Extract the file path and line range directly from this. This is the primary way users will invoke /ask — they select code, then type something like "/ask why is this like that" without naming the file or lines.

    b) Explicit file/line references — "on line 42", "lines 10-50 of src/main.rs" → use directly.

    c) Named symbol — mentions a variable/function/class → Read the file, find where it's defined, extract line numbers.

    d) File without line specifics → whole file (omit --lines).

    e) No file, no lines, no selection context, no identifiable code reference → Do NOT attempt to guess or search. Just reply:

    Select some code or mention a specific file/symbol, then /ask your question.

    Stop here. Do not spawn a subagent.

  2. Spawn one subagent with the template below. Use max_turns: 4.

  3. Relay the answer to the user. That's it.

Subagent Configuration

Task tool settings:
  subagent_type: "general-purpose"
  max_turns: 4

The subagent gets only Bash and Read. It does NOT get Glob, Grep, or Task. It runs at most 4 turns — this is a fast lookup, not a research project.

If you want to read an entire file or range of lines AND the corresponding prompts behind them, use git-ai blame --show-prompt. This is better than search for this use case — it gives you every line's authorship plus the full prompt JSON in one call.

Read the full file on GitHub · 141 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 141 lines · 54 tokens per session scan A b9bb8bd00413

Subscribe to this mod's changes

ask is a skill published in the GitHub repository git-ai-project/git-ai (2,525 stars, last pushed today), licensed Apache-2.0. It adds 54 tokens to every session and 1,482 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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