social-response

social-response is a command for Claude Code from nimbalyst/nimbalyst. It costs 17 tokens per session (2,070 once invoked), scanned A, original, MIT.

A command for drafting replies to messages from Discord, Twitter, Reddit, GitHub Discussions, email, or other social channels.

In plain words
What is it for?
It helps prepare friendly, copy-ready answers to support questions and complaints, while deciding whether unsupported feature requests should be pursued.
Why use it?
It reduces the work of understanding a request, checking whether Nimbalyst supports it, and matching replies to responses approved before.

Command for Claude Code

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 commands/nimbalyst/nimbalyst/social-response
Clone the repo
git clone --depth 1 https://github.com/nimbalyst/nimbalyst

Made for: Claude Code.

Wrote 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.

agentmods badge for social-response

README.md
[![agentmods](https://agentmods.dev/badge/commands/nimbalyst/nimbalyst/social-response.svg)](https://agentmods.dev/commands/nimbalyst/nimbalyst/social-response)
Your own site
<a href="https://agentmods.dev/commands/nimbalyst/nimbalyst/social-response"><img src="https://agentmods.dev/badge/commands/nimbalyst/nimbalyst/social-response.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,070 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 $0.00017 $0.02070
Opus 5 $0.00009 $0.01035
Sonnet 5 $0.00003 $0.00414
Haiku 4.5 $0.00002 $0.00207

Measured 4d ago against content hash aec0812c71be, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

social-response 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 4d 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.

.claude/commands/social-response.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/social-response Command

Draft a response to a user reaching out on Discord or another social channel.

User's Message

$ARGUMENTS

What This Command Does

The user pastes a message from Discord, Twitter, Reddit, GitHub Discussions, email, or another social channel. Your job is to:

  1. Figure out what they're asking for or complaining about
  2. Determine whether Nimbalyst already supports it
  3. If yes -- draft a friendly, copy-paste-ready response explaining how
  4. If no -- decide whether it's a good idea, then ask the user how to proceed using AskUserQuestion

Process

Step 1: Read the response log

Before drafting anything, read nimbalyst-local/social/social-response.jsonl if it exists. Each line is a previously-approved response. Skim the last 20-30 entries for:

  • Tone calibration -- how does the user actually phrase replies?
  • Recurring requests -- has someone asked something similar before? What did we tell them?
  • Stock answers -- if a feature comes up repeatedly (e.g. "how do I switch themes"), reuse and refine the prior wording.

If the file doesn't exist yet, that's fine -- proceed without it. Do not create the file at this stage; it's only written after the user approves a draft.

Step 2: Understand the request

Read the pasted message. Extract:

  • What are they trying to do? (the underlying goal, not just the literal words)
  • What channel are they on? (tone shifts: Discord is casual, GitHub is more formal)
  • Is this a question, a feature request, a bug report, or general feedback?

If the message is too vague, note that and recommend asking them a clarifying question before responding.

Step 3: Check whether Nimbalyst already supports this

Investigate before drafting. Common moves:

  • Read docs/FEATURE_INVENTORY.md -- the canonical list of what Nimbalyst can do
  • Search the docs: docs/, packages/*/CLAUDE.md, and any topic-specific doc listed in the root CLAUDE.md
  • Search the codebase with Grep/Glob for the feature, setting, or behavior they're describing
  • Check existing trackers with tracker_list({ search: "..." }) -- this may already be a known idea, in-progress work, or a logged decision (including a decision NOT to build it)
  • Check the changelog (CHANGELOG.md) -- the feature may have shipped recently

Read the full file on GitHub · 167 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. 4d ago First seen · 167 lines · 17 tokens per session scan A aec0812c71be

Subscribe to this mod's changes

social-response is a command published in the GitHub repository nimbalyst/nimbalyst (1,643 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 2,070 once invoked, about $0.0001 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.