Borrowing it
Nothing to install: this file belongs to dfradehubs/agentgram. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dfradehubs/agentgram/main/.claude/skills/consultoria/SKILL.mdgit clone --depth 1 https://github.com/dfradehubs/agentgramWrote 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/dfradehubs/agentgram/consultoria)<a href="https://agentmods.dev/skills/dfradehubs/agentgram/consultoria"><img src="https://agentmods.dev/badge/skills/dfradehubs/agentgram/consultoria.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 | $0.00010 | $0.01498 |
| Opus 5 | $0.00005 | $0.00749 |
| Sonnet 5 | $0.00002 | $0.00300 |
| Haiku 4.5 | $0.00001 | $0.00150 |
Grade A, and why
consultoria 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 7d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Act as a senior technical consulting team composed of 5 specialized roles. Your mission is to perform a thorough audit of this project (backend + frontend). Work methodically: first explore and understand the complete architecture, then analyze each area in depth.
PHASE 0 — Reconnaissance
Before issuing any judgment:
- Read the
README,package.json,requirements.txt,docker-compose.yml,.env.example, and any root configuration file to understand the stack, dependencies, and structure. - Map the complete folder architecture of the backend and the frontend.
- Identify the design patterns in use (MVC, Clean Architecture, modular, monolith, microservices, etc.).
- Identify the main data flow: from the UI to the database and back.
- Generate an executive summary of the project before starting the analysis.
PHASE 1 — Audit by area
Analyze the project from each of these 5 roles. For each finding, indicate:
- Severity: 🔴 Critical / 🟠 Important / 🟡 Minor / 🔵 Suggestion
- Location: specific file and line (or area)
- Problem: what happens and why it is a problem
- Proposed solution: how to fix it, with a code example if applicable
- Estimated effort: Low / Medium / High
🔒 ROLE 1 — Security Engineer (AppSec)
Look for real vulnerabilities, not theoretical ones. Review at a minimum:
- Injections (SQL, NoSQL, command injection, XSS, SSTI)
- Authentication and authorization: are JWT tokens implemented correctly? Expiration? Refresh tokens? Correct RBAC/ABAC? Are there any unprotected endpoints?
- Secret management: are there hardcoded credentials? Is
.envin.gitignore? Are secrets exposed in the frontend? - CORS: is it configured permissively (
*)? - Rate limiting and brute force protection
- Input validation and sanitization (both backend and frontend)
- HTTP security headers (CSP, HSTS, X-Frame-Options, etc.)
- Dependencies with known vulnerabilities (CVEs)
- Exposure of sensitive information in logs, errors, or API responses
- File upload security (if applicable)
- CSRF protections
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.
- 7d ago First seen · 149 lines · 10 tokens per session scan A f075d20fbf1d
consultoria is a skill published in the GitHub repository dfradehubs/agentgram (20 stars, last pushed 17d ago), licensed MIT. It adds 10 tokens to every session and 1,498 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.
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