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    Username OSINT Hunter Skil

    1

    A structured OSINT workflow for Maigret to find, verify, and document username footprints across public services.

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    Username OSINT Hunter Skil

    Username OSINT Hunter Skil

    Example session with this skill installed

    I need to run a brand audit for the username 'cybersec_corp_dev' to see where our handle is registered. Give me a search plan and a report template.

    • Read your context and instructions
    • Compiled the username osint hunter

    I have drafted a targeted search plan and the corresponding report structure for your brand audit. This approach focuses on high-confidence matches and respects service rate limits.

    Username Audit Plan: cybersec_corp_dev

    1. Objective and Scope

    • Purpose: Brand handle availability and impersonation check.
    • Subject: 'cybersec_corp_dev' (Corporate Brand).
    • Exclusions: Private networks, internal-only portals.

    2. Execution Command

    
    # Recommended command for bounded search
    maigret cybersec_corp_dev --timeout 20 --retries 2
    

    3. Triage Ledger Template

    ServicePublic Profile URLStatusEvidence/NotesConfidence
    GitHubhttps://github.com/cybersec_corp_devLikely LiveMatches official repo linksHigh
    Twitter/Xhttps://x.com/cybersec_corp_devLikely LiveVerified brand bioHigh
    Instagramhttps://instagram.com/cybersec_corp_devPossibleNo bio content; needs reviewMedium
    PyPihttps://pypi.org/user/cybersec_corp_devFalse PositiveGeneric placeholder pageLow

    4. Cross-Reference Observations

    • Bio Alignment: Check if the profile description matches the official "Securing the future" tagline.
    • Reciprocal Links: Look for links pointing back to the primary corporate domain.
    • Visual Identity: Note if the official logo is used consistently across high-confidence hits.

    Next steps

    1. Run the maigret command in your local terminal.
    2. Populate the Triage Ledger with the raw output.
    3. Review 'Possible' hits for any links to external sites.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Finding where a username appears across the web often results in a mess of 404s, false positives, and unverified data. This skill provides a structured workflow for using Maigret to conduct responsible username OSINT, filtering out noise and documenting evidence with high confidence.

    What it does

    • Environment setup Provides safe installation steps for Maigret using isolated Python virtual environments.
    • Search planning Defines bounded search parameters to avoid rate limits and respect service restrictions.
    • Result triage Classifies output into likely live, possible, dead, or false positive categories.
    • Evidence documentation Creates a ledger for each result including URLs, timestamps, and observed public signals.
    • Confidence scoring Evaluates the likelihood of account connection based on cross-referenced public data.
    • Reporting Generates a structured OSINT report including methodology, summary counts, and evidence tables.

    How it works

    1. Define scope Record the authorized objective, target username, and excluded services to ensure compliance.
    2. Execute search Run narrow, bounded commands via Maigret to collect raw profile data.
    3. Analyze results Filter out 404s, generic pages, and ambiguous matches to find high-confidence profiles.
    4. Cross-reference Compare public profile descriptions and links to verify if accounts belong to the same entity.

    Frameworks & tools

    This skill is built for the Maigret OSINT tool and requires a Python environment. It assumes access to a CLI for execution.

    Why this beats prompting it yourself

    Standard prompts often fail to distinguish between a service timeout and a deleted account. This skill enforces a rigorous classification logic that prevents false positives from polluting your research. It moves beyond raw data collection by requiring multi-signal verification before asserting a match.

    Use cases

    • Digital footprint audit Discover where your personal handles are publicly visible.
    • Brand protection Monitor for impersonation or squatting of corporate handles across new platforms.
    • Handle availability Check name availability across hundreds of services for a new project launch.
    • Authorized investigation Conduct public-interest research with a repeatable, evidence-based methodology.

    Known limitations

    Does not bypass CAPTCHAs, login walls, or privacy controls. It requires a local execution environment to run Maigret and does not perform real-time web scraping on its own.

    Requires local Python environment and Maigret installation. Does not bypass login walls or CAPTCHAs. Results are leads, not proof of identity.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Recently published to Agensi

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    Trust & safety

    Security scan

    Security scan passed 13 days ago

    Software
    Python

    Permissions

    Terminal / Shell
    Write Files
    Listed13 days ago

    What's inside

    Frequently Asked Questions

    This skill provides a structured framework that automates the triage of Maigret results, using specific logic to distinguish between genuine account matches, service timeouts, and false positives that standard searches often miss.

    The skill requires a Python environment and the Maigret OSINT tool; it is designed for use with AI agents capable of executing CLI commands or providing structured technical guidance.

    You will receive the complete OSINT workflow logic, environment setup protocols, result classification templates, and reporting structures needed to perform high-confidence username investigations.

    No, this skill is designed for ethical OSINT and does not bypass CAPTCHAs, paywalls, or private account settings; it only aggregates and verifies data that is already publicly accessible.

    The skill includes a dedicated step for 'Confidence Scoring' where it cross-references public profile bios, links, and activity signals to verify if multiple accounts actually belong to the same entity.

    While the logic is robust, you will need to manually update your local Maigret installation periodically to ensure the tool's site-specific parsers remain compatible with changing web platforms.

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