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 unbounce/agent-plugins --skill mcp-feedbackgit clone --depth 1 https://github.com/unbounce/agent-pluginsWrote 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/unbounce/agent-plugins/mcp-feedback)<a href="https://agentmods.dev/skills/unbounce/agent-plugins/mcp-feedback"><img src="https://agentmods.dev/badge/skills/unbounce/agent-plugins/mcp-feedback/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/unbounce/agent-plugins/mcp-feedback"><img src="https://agentmods.dev/badge/skills/unbounce/agent-plugins/mcp-feedback.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00146 | $0.01117 |
| Opus 5.5 | $0.00058 | $0.00447 |
| Sonnet 5.5 | $0.00029 | $0.00223 |
| Haiku 4.5 | $0.00015 | $0.00112 |
Grade A, and why
mcp-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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Submit Unbounce MCP feedback
Record the user's feedback about the Unbounce MCP tools to the team's store by
calling the submit_feedback tool. The tool persists the record server-side, so
nothing has to be copied out of the conversation into Slack or anywhere else.
The
mcp-prefix here means "pertains to Unbounce MCP," not "about a page." This skill is about capturing feedback on the MCP tools themselves — whether they broke, delighted, confused, or fell short.
Hard rule: report, don't repair
Do NOT try to fix, retry, or work around the thing being reported. This skill
records feedback on what already happened. Never invent tool-call arguments or error
text — anything not actually present is unknown. (Fixing the underlying task, if the
user wants that, is separate work done after the feedback is recorded.)
1. Gather the feedback
Settle two things — from the conversation where possible, asking only what you can't infer:
type— one ofbug·praise·feature_request·confusion·other.message— the feedback in the user's own words. Keep it faithful; don't editorialize.
For a bug, also assemble the context: the verbatim failing tool call(s)
from the transcript — exact tool name, exact arguments JSON, and the raw result/error
text (call out any code/reason/remedy fields). Include the relevant one(s),
especially the failing call. If the failure happened in another session and isn't in
the transcript, ask a couple of targeted questions and mark transcript-only fields
(exact arguments, exact raw error) as unknown. For non-bug types, context is
usually unnecessary — include a light pointer (the tool or page in question) only if
it genuinely helps.
Login / connection problems are a bug: capture what the user was doing, the
client they're in, and the exact error text (e.g. access denied, invalid_grant, a
failed redirect, repeated re-login prompts). Note that if the MCP can't connect at
all, submit_feedback itself won't be reachable — that's expected, and step 4's
inline fallback is how the feedback still gets out.
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.
- 2mo ago First seen · 88 lines · 146 tokens per session scan A 020e579eeb7b
mcp-feedback is a skill published in the GitHub repository unbounce/agent-plugins (2 stars, last pushed 5d ago), licensed MIT. It adds 146 tokens to every session and 1,117 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
mcp-feedback compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mcp-feedbackunbounce/agent-plugins | Skill | 2 | 5d ago | MIT | A | 146 | Claude Code |
| 04-script-videominhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 154 | Claude Code |
| 21-audit-ads-performanceminhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 238 | Claude Code |
| 23-personal-brand-strategy-globalminhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 177 | Claude Code |
| 24-ai-avatar-production-globalminhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 174 | Claude Code |
| 26-thought-leadership-content-globalminhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 167 | Claude Code |
| 26-thought-leadership-contentminhnv0807/ai-business-skills | Skill | 643 | 3d ago | MIT | A | 216 | Claude Code |