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 KirKruglov/claude-skills-kit --skill report-analyzergit clone --depth 1 https://github.com/KirKruglov/claude-skills-kitWrote 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/kirkruglov/claude-skills-kit/report-analyzer)<a href="https://agentmods.dev/skills/kirkruglov/claude-skills-kit/report-analyzer"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/report-analyzer/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/kirkruglov/claude-skills-kit/report-analyzer"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/report-analyzer.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 | $0.00184 | $0.01807 |
| Opus 5 | $0.00092 | $0.00903 |
| Sonnet 5 | $0.00037 | $0.00361 |
| Haiku 4.5 | $0.00018 | $0.00181 |
Grade A, and why
report-analyzer 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 10d 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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Report Analyzer
Analyzes large reports (PDF, PPTX) and produces a structured summary with key data and insights.
Target audience: product managers, marketers, analysts, finance professionals, C-level executives.
Language Detection
Detect the language from the user's message. Use that language for all output — the summary document, clarifying questions, and responses. If the user writes in Russian, respond and generate the output in Russian. If in English — in English.
Input
- A PDF or PPTX report file
- The user specifies the file name or path in their message, or uploads the file directly
Output
A structured summary document (up to 1.5 pages) containing:
- Report metadata
- Executive Summary
- Key figures and data
- Key insights
- Report structure
Instructions
Step 1 — Locate the input file
The user specifies the report file name in their message. Locate the file using this order:
- Check the current working directory and subdirectories (e.g.
input/folder or project root) - If the user provided a full path — use it directly
File search:
find . -iname "*.pdf" -o -iname "*.pptx" 2>/dev/null
If the file is not found — ask the user:
"Please specify the exact file name or path to the report, or upload the file directly. Supported formats: PDF, PPTX."
If the format is not supported:
"This skill works with PDF and PPTX files. Please provide a file in one of these formats."
Step 2 — Ask clarifying questions
Ask the user the following questions before proceeding:
Question 1: "What is the analysis focus?"
- General overview
- Numbers and data
- Strategic takeaways
- Everything combined
Question 2: "What output file format do you prefer?"
- .md
- .docx
Do not create the output file until both questions are answered.
Step 3 — Read and process the file
For PDF:
import pdfplumber
with pdfplumber.open("path/to/file.pdf") as pdf:
text = ""
for page in pdf.pages:
text += page.extract_text() or ""
# Extract tables
tables = page.extract_tables()
What ships with it
4 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.
- 10d ago First seen · 258 lines · 184 tokens per session scan A 981df30f6652
report-analyzer is a skill published in the GitHub repository KirKruglov/claude-skills-kit (18 stars, last pushed 1mo ago), licensed MIT. It adds 184 tokens to every session and 1,807 once invoked, about $0.0009 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.
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