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.
npx skills add aeonfun/aeon --skill reply-makergit clone --depth 1 https://github.com/aeonfun/aeonWrote 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/aeonfun/aeon/reply-maker)<a href="https://agentmods.dev/skills/aeonfun/aeon/reply-maker"><img src="https://agentmods.dev/badge/skills/aeonfun/aeon/reply-maker.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 15 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Data Exfiltration · line 90 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 359 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 79 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 90 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 354 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 362 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.06452 |
| Opus 5 | $0.00023 | $0.03226 |
| Sonnet 5 | $0.00009 | $0.01290 |
| Haiku 4.5 | $0.00005 | $0.00645 |
Grade C, and why
reply-maker scanned grade C with 2 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- autoresearch: variation B — sharper output via specificity gates, anti-sycophancy lint, post-write self-edit, and skip-gate for low-leverage tweets --> Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Path A — X.AI API (primary).** `XAI_API_KEY` is injected into this skill's environment (declared in `requires:`), so the direct `curl` to `https://api.x.ai/v1/responses` is the primary fetch path (full contract in **Fe Copies of this mod
1 near-identical copy found in the catalogue:
- reply-maker — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
${var} — selects the mode and scope:
- empty → Mode A (Reply Drafting): auto-discover reply-worthy tweets across your areas of interest (from recent logs + memory) and draft two reply options for each.
@handle/ numeric X list ID / topic → Mode A (Reply Drafting) scoped to that handle, list, or topic.from-logs(or--from-logs, optionally followed by an@handleor project name to narrow the scan) → Mode B (From-Logs Engagement): scan recent logs for flagged engagement opportunities and turn them into copy-paste-ready responses.revise:<instruction>→ Revise branch: reload the last drafted replies and refine them per the instruction (the Telegram force-reply shape, e.g.revise:make them shorter).
Preamble (both modes)
Read memory/MEMORY.md for context on active projects and open engagement follow-ups.
Then read memory/logs/ — the window depends on the mode:
- Mode A: the last 2 days of
memory/logs/for recentlist-digest,tweet-roundup, and priorreply-makeroutputs (used as a candidate pool and for reply de-duplication). - Mode B: the last 7 days of
memory/logs/for engagement opportunities flagged by other skills (project-pulse,refresh-x,reply-maker,channel-recap) or noted in MEMORY.md "Known Follow-ups".
Parse ${var} to pick the branch (trim whitespace, compare case-insensitively):
- If
${var}starts withrevise:— run the Revise branch (below) and stop. This is the shapescripts/telegram-route.shsends when the operator replies to a "refine these replies?" force-reply prompt; catch it before mode parsing. - If
${var}isfrom-logsor--from-logs— optionally followed by a whitespace-separated@handleor project name — run Mode B (From-Logs Engagement). Treat any trailing token as an optional filter that narrows the opportunity scan to that handle/project. - Otherwise run Mode A (Reply Drafting), treating
${var}as the scope: empty,@handle, numeric X list ID, or a topic string.
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 · 374 lines · 45 tokens per session scan C e5e47f590f2a
reply-maker is a skill published in the GitHub repository aeonfun/aeon (718 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 6,452 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (hidden instructions, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
flowcraft-config
Author, validate, and troubleshoot complete FlowCraft deployment configuration (deploy.yaml with the runtime section, inference/workspace/sandbox/tool sub-documents, core/memory contracts, and graph JSON node wiring). Use when writing or reviewing FlowCraft configs, assembling an agent deployment, adding…
api-interface-design
Use when designing public APIs, module boundaries, provider adapters, tool schemas, or data contracts.
unit-converter
Converts values between metric and imperial units, using the project's agreed factors.
explore
Explore the codebase and summarize how the project is wired.
flow-define
Multi-AI requirements scoping using Codex and Gemini CLIs (Double Diamond Define phase). Use when: AUTOMATICALLY ACTIVATE when user requests clarification or scoping:. "define the requirements for X". "clarify the scope of Y".
flow-develop
Multi-AI implementation using Codex and Gemini CLIs (Double Diamond Develop phase). Use when: AUTOMATICALLY ACTIVATE when user requests building or implementation:. "build X" or "implement Y" or "create Z". "develop a feature for X".