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 alexsvdk/gigaplexity-mcp --skill gigaplexity-file-intelligencegit clone --depth 1 https://github.com/alexsvdk/gigaplexity-mcpWrote 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/alexsvdk/gigaplexity-mcp/gigaplexity-file-intelligence)<a href="https://agentmods.dev/skills/alexsvdk/gigaplexity-mcp/gigaplexity-file-intelligence"><img src="https://agentmods.dev/badge/skills/alexsvdk/gigaplexity-mcp/gigaplexity-file-intelligence/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/alexsvdk/gigaplexity-mcp/gigaplexity-file-intelligence"><img src="https://agentmods.dev/badge/skills/alexsvdk/gigaplexity-mcp/gigaplexity-file-intelligence.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 | $0.00060 | $0.00899 |
| Opus 5 | $0.00030 | $0.00449 |
| Sonnet 5 | $0.00012 | $0.00180 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
gigaplexity-file-intelligence 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 12d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gigaplexity File Intelligence Skill
Purpose
Use this skill to extract reliable insights from user files (docs/images/audio), then produce concise, structured outputs aligned with the task (summary, Q&A, comparison, due diligence, extraction).
MUST Use When
Use this skill immediately if user intent includes any of these:
- “прочитай/разбери файл”, “что в этом PDF/DOC?”, “проанализируй картинку/аудио”.
- Need to summarize or compare attached/local files.
- Need factual extraction from file content (entities, dates, obligations, risks, action items).
- Need multimodal understanding (document + image, or image-only, audio-only).
Core Capability Constraint (critical)
Gigaplexity ask supports attachments, but all files in one request must be from the same category:
- Document/text/code files
- Images
- Audio
If user gives mixed categories, split into multiple passes and then synthesize.
Workflow
1) Input Validation
- Ensure file paths are absolute and files exist.
- Determine category for each file.
- If categories mixed: batch by category and process separately.
2) Intent Clarification (if needed)
Ask minimal clarifying questions only when output target is ambiguous:
- summary vs extraction vs comparison vs risk review
- desired language and level (brief / detailed)
3) File Analysis via Gigaplexity
- Use
#tool:gigaplexity/askwithfile_paths. - Provide a precise task prompt (what to extract, what to ignore, desired format).
- For large/complex files, run iterative passes:
- pass A: global summary
- pass B: targeted extraction
- pass C: contradiction/risk scan
4) Verification Pass
- For high-stakes tasks (legal/finance/security), request explicit evidence snippets from file content.
- If content is unclear, state uncertainty and what additional file/context is needed.
5) Synthesis
- Merge per-file or per-batch findings.
- Highlight agreements, conflicts, missing info, and next actions.
Prompt Patterns (ready to use)
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.
- 12d ago First seen · 99 lines · 60 tokens per session scan A d093bebc5697
gigaplexity-file-intelligence is a skill published in the GitHub repository alexsvdk/gigaplexity-mcp (6 stars, last pushed 2mo ago), licensed MIT. It adds 60 tokens to every session and 899 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.
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