MiMoCode is a terminal-based AI coding assistant that reads and writes code, runs commands, manages Git, and remembers project context across sessions. Developers use it to work with software projects through a command-line interface and connect it to language-model providers; the catalogue includes skills and instructions for it.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/XiaomiMiMo/MiMo-Codenpx agentmods add skills/xiaomimimo/mimo-code/get-rep-call-feedbackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xiaomimimo/mimo-code/get-rep-call-feedback)<a href="https://agentmods.dev/skills/xiaomimimo/mimo-code/get-rep-call-feedback"><img src="https://agentmods.dev/badge/skills/xiaomimimo/mimo-code/get-rep-call-feedback.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.02310 |
| Opus 5 | $0.00023 | $0.01155 |
| Sonnet 5 | $0.00009 | $0.00462 |
| Haiku 4.5 | $0.00005 | $0.00231 |
Grade A, and why
get-rep-call-feedback 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- get-rep-call-feedback — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Get Rep Call Feedback
Context-Gathering Intake
Whenever this skill asks for context, strongly prefer using the answers-ask-user-input skill and the ask_user_input tool over other tools such as request_user_input; otherwise ask directly in the conversation.
Turn grounded call evidence into practical coaching for one rep. This skill compares the target rep with relevant peer examples, extracts repeatable moves, and maps them to exact moments the target rep can improve. It owns the coaching readout only; it does not create scorecards, send feedback, post messages, or save coaching artifacts.
Common Skill Instructions
MANDATORY: If not already in context, read and adhere closely to plugins/sales/skills/index/SKILL.md## Cross-Skill Best Practices.
Key Dependency Categories
These categories are particularly important for this workflow; use other sources only when they materially improve call selection or coaching context.
- [Blocking] ~~Meeting Transcripts for target and peer call search, summaries, transcript moments, speaker context, dates, companies, and clickable call links. It blocks the default live-source feedback path; explicit transcript-like call evidence already in context satisfies the need.
- ~~Knowledge & Files for user-provided or exported transcripts, call notes, manager examples, and prior coaching context
Transcript-like call evidence is required for behavioral claims. Manager notes, CRM outcomes, and generic impressions can shape focus, but cannot substitute for observed call evidence. If live transcripts are unavailable, continue from sufficiently detailed pasted or exported material and label the coverage limit.
Reference Loading
SKILL.md owns the normal benchmarked-coaching loop and output format. Load references only when their extra detail matters:
- Use references/call-transcripts-connector-playbook.md when date-window conversion, attendee-filter limitations, threshold fallback, or sparse-result recovery needs more detail.
- Use references/request-schema.yaml for structured input normalization.
- Use references/source-priority.md when evidence quality is mixed.
- Use references/output-contract.md when checking required sections or downstream compatibility.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 168 lines · 45 tokens per session scan A 6722491c123e
get-rep-call-feedback is a skill published in the GitHub repository XiaomiMiMo/MiMo-Code (12,958 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 2,310 once invoked, about $0.0002 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 2026-09-03.
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