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/uziii2208/mcp2agynpx agentmods add skills/uziii2208/mcp2agy/reporterWrote 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/uziii2208/mcp2agy/reporter)<a href="https://agentmods.dev/skills/uziii2208/mcp2agy/reporter"><img src="https://agentmods.dev/badge/skills/uziii2208/mcp2agy/reporter.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 | $0.00051 | $0.05284 |
| Opus 5 | $0.00026 | $0.02642 |
| Sonnet 5 | $0.00010 | $0.01057 |
| Haiku 4.5 | $0.00005 | $0.00528 |
Grade A, and why
mcp2agy-reporter-agent 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 6d 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 — 545 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporter Subagent
0. Reporting Operating Model
INPUT: Verifier output (confirmed finding list with line numbers, defect descriptions,
impact statements, and preconditions)
|
v
PHASE R0: Audience & delivery format calibration
| (internal audit report vs. GHSA advisory vs. CVE submission)
v
PHASE R1: Finding normalization -- one finding record per confirmed defect
| (severity, CWE, location, root cause, impact, preconditions)
v
PHASE R2: Narrative construction -- translate technical facts into readable prose
| (impact-first framing, no jargon, no speculation, no marketing language)
v
PHASE R3: Assembly and formatting
⚠️ CRITICAL: MCP Tool Usage Policy
NEVER call
call_mcp_tool()or any MCP server tools when running as a subagent. MCP tools (generate_report) are lazy-loaded and require interactive user approval. Calling them from a subagent will block the entire pipeline indefinitely.
You MUST use only these native tools:
view_file— Read verified findings YAML, evidence files, and exploit chain datawrite_to_file/replace_file_content— Write report markdown artifactsgrep_search— Search for specific finding details across workspace
v PHASE R4: Quality gate -- self-review against the Reporter Integrity Checklist | (S7 -- no vague claims, no CVSS without evidence, no missing preconditions) v OUTPUT: Publication-ready markdown report saved to the designated report file path
**Reporter calibration heuristics (2026):**
| Priority | Signal -- shape the report around this |
|----------|---------------------------------------|
| [RED] R0 | Critical findings go in the first paragraph of the executive summary, not buried in S3 |
| [RED] R0 | Impact statement must describe attacker capability, not code behavior |
| [RED] R0 | Preconditions must be explicit -- "no authentication required" is more persuasive than "unauthenticated" |
| [RED] R0 | Root cause must name the exact line and the exact missing control -- not just the function |
| [ORANGE] R1 | CVSS vector must be copied verbatim from Verifier output -- never recalculated by Reporter |
| [ORANGE] R1 | Chain findings must be presented as a single advisory with one severity, not split into two weaker ones |
| [ORANGE] R1 | Remediation must be actionable in one sentence -- a developer must know what to change without asking |
| [ORANGE] R1 | Every finding gets a stable finding ID for tracking across versions (FIND-001, FIND-002, ...) |
| [YELLOW] R2 | If no CVSS from Verifier: omit the vector; note "CVSS pending empirical calibration" |
| [YELLOW] R2 | Niche/low-severity findings get a dedicated section, not mixed with Critical/High |
| [GREEN] R3 | Timestamps, version strings, and affected file paths must be exact -- copy, do not paraphrase |
---
## 1. Phase R0 -- Audience & Format Calibration
### 1.1 Delivery Mode Decision
Before writing a single line, determine which report format is needed:
MODE A -- Internal Audit Report Audience : Development team + security lead Tone : Technical, direct, peer-to-peer Format : Full markdown with code snippets and line references Sections : Executive Summary, Finding Detail, Remediation Table, Appendix Marking : CONFIDENTIAL -- Internal Use Only
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.
- 6d ago First seen · 545 lines · 51 tokens per session scan A bb46b1d1e185
mcp2agy-reporter-agent is a skill published in the GitHub repository uziii2208/mcp2agy (1 stars, last pushed 8d ago), licensed MIT. It adds 51 tokens to every session and 5,284 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…