What is skillport AGENTS.md?

Repository guidance for Skillport, including rules for planning, indexing, fallback search, logging, documentation, and code structure. A fallback chain is a sequence of backup methods used when the preferred search method is unavailable.

It guides agents building or changing task plans, category and tag handling, vector and text search, MCP communication, and shared helper code.

It helps keep search behaviour, configuration defaults, logs, plans, and documentation consistent across the project.

How gotalab/skillport configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to gotalab/skillport. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/gotalab/skillport/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/gotalab/skillport

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/gotalab/skillport/agents-md/github.svg)](https://agentmods.dev/instructions/gotalab/skillport/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/gotalab/skillport/agents-md"><img src="https://agentmods.dev/badge/instructions/gotalab/skillport/agents-md/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/gotalab/skillport/agents-md"><img src="https://agentmods.dev/badge/instructions/gotalab/skillport/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 813 This file is loaded in full into every session.

When invoked 813 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00813	$0.00813
Opus 5.5	$0.00325	$0.00325
Sonnet 5.5	$0.00163	$0.00163
Haiku 4.5	$0.00081	$0.00081

Measured 2mo ago against content hash 741d2ac2a338, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

skillport AGENTS.md 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 2mo 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.

AGENTS.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Guidelines & Context

1. Core Principles (10-second recall)

PLAN.md: SSOT for「どう作るか」(how to build); keep tasks in docs/latest/PLAN.md, update continuously, snapshot at release.
Task tracking: Use checkbox lists (- [ ]/- [x]); include Task ID for larger work.
Safe defaults: Default EMBEDDING_PROVIDER=none; when enabling external providers, fail fast on missing keys.
Normalization: Always trim+lowercase category/tags for indexing, filtering, and search.
Fallback chain: Preserve vector → FTS → substring fallback; never break the chain.
MCP logging: stdout is JSON-RPC only; send all logs/debug to stderr.
Behavioral regression tests (golden traces): Not required now; add for critical flows when ready.
Refactoring style: Prefer function-based design with dict dispatch over class-based Strategy/ABC patterns. Keep helpers small; share common logic via helper functions, not inheritance.
Docs governance: See docs/AGENTS.md for layout/roles; docs/steering/OPERATING_MODEL.md for doc/release ops; docs/steering/ENGINEERING_GUIDE.md for technical policy; docs/steering/RUNBOOK.md for operational steps.

2. Project Context

Architecture

Brand: SkillPort
Packages: skillport (CLI), skillport-mcp (MCP server), skillport-core (shared lib)
Type: CLI + MCP Server (Model Context Protocol)
Stack:
- Runtime: Python 3.10+
- Package Manager: uv
- MCP Lib: fastmcp
- Database: lancedb (Vector + FTS)
- Config: pydantic-settings

Directory Structure

packages/skillport-core/src/skillport/: Source code (modular monolith)
- interfaces/cli/: Typer CLI adapter
- interfaces/mcp/: FastMCP server adapter
- modules/skills/: Skill management public/internal APIs
- modules/indexing/: Index build/query logic
- shared/: Config, types, utils, exceptions
docs/latest/: Living documentation (SSOT)
docs/releases/vX.Y.Z/: Release snapshots (frozen)
docs/steering/: Governance & guides
.skills/: Local skills storage for testing
verify_server.py: Verification script (Mock Client)

Read the full file on GitHub · 58 lines

Changes

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.

2mo ago First seen · 58 lines · 813 tokens per session scan A 741d2ac2a338

Subscribe to this mod's changes

skillport AGENTS.md is an instructions file published in the GitHub repository gotalab/skillport (421 stars, last pushed 12d ago), licensed MIT. It adds 813 tokens to every session, about $0.0033 per session on Opus 5.5. 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.

agent-skills ai-agent claude codex context-engineering github-copilot

skillport AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
skillport AGENTS.mdgotalab/skillport	Instructions file	421	12d ago	MIT	A	813	Codex, OpenCode
awesome-ai-setup riverpod.instructions.mdshuchitajain/awesome-ai-setup	Instructions file	5	5mo ago	MIT	A	1,742	GitHub Copilot
awesome-ai-setup testing.instructions.mdshuchitajain/awesome-ai-setup	Instructions file	5	5mo ago	MIT	A	1,712	GitHub Copilot
awesome-ai-setup widgets.instructions.mdshuchitajain/awesome-ai-setup	Instructions file	5	5mo ago	MIT	A	1,263	GitHub Copilot
awesome-ai-setup copilot-instructions.mdshuchitajain/awesome-ai-setup	Instructions file	5	5mo ago	MIT	A	1,020	GitHub Copilot
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode

skillport: Instructions file for Codex