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 agentmods add skills/samplexbro/agentsmesh/add-agent-targetnpx skills add sampleXbro/agentsmesh --skill add-agent-targetgit clone --depth 1 https://github.com/sampleXbro/agentsmeshWrote 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/samplexbro/agentsmesh/add-agent-target)<a href="https://agentmods.dev/skills/samplexbro/agentsmesh/add-agent-target"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/add-agent-target.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 | $0.00062 | $0.01880 |
| Opus 5 | $0.00031 | $0.00940 |
| Sonnet 5 | $0.00012 | $0.00376 |
| Haiku 4.5 | $0.00006 | $0.00188 |
Grade A, and why
add-agent-target 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 3d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Add Agent Target
Use this skill when the task is to add a brand-new supported agent target to this repository (built-in) or as an external plugin package.
Primary reference: docs/add-new-target-playbook.md is the step-by-step workflow (phases 1–9, file templates, verification gates). Open it first and follow it. This skill file is the contract — the non-negotiable rules, touchpoints, and completion bar. The playbook is how; this file is what and why.
Companion skill: add-global-mode-target — use only when extending global-mode support into an existing target that was built before global was a first-class contract. For new targets, global mode is part of this skill (scaffold wires it automatically).
When To Use
- The task is to add a tool not currently in
src/targets/catalog/target-ids.ts - Scope covers both
projectandglobalmodes unless the target has no meaningful global surface - Delivery is either built-in (in this repo) or external plugin (standalone npm package)
Do Not Use This Skill For
- Extending global-mode coverage on an existing target — use
add-global-mode-target - Changing capability levels for an existing target — update the target's descriptor directly
- Plugin feature work that doesn't add a new target id
Non-Negotiable Rules
MUST
- Search the internet for the target's current official file structure, config files, and example content before changing code.
- Prefer official docs and other primary sources. Use vendor examples or source code only when official docs are incomplete, and call that out explicitly.
- Separate the target product from the current assistant runtime before making format decisions. Do not confuse a generated target like
codex-cliwith Codex desktop/chat, or local CLI MCP config with app-managed connectors. - Capture the target's real capability map for every canonical feature: rules, additionalRules, commands, agents, skills, mcp, hooks, ignore, permissions.
- Fill in the descriptor
metadatablock (displayName,category,officialUrl,shortDescription). This is required at compile time and drives every auto-generated tool list in README + website. The scaffold leavesTODO(agentsmesh-scaffold)markers — replace them with the values from your Phase 1 research before commit. - When a feature is
nonebutskillsisnativeorembedded, evaluate whethersupportsConversionshould project that feature as skills. If the target reads skill bundles, commands and agents with no native surface should be projected as skills viasupportsConversion: { commands: true, agents: true }and registered insrc/config/core/conversions.tswithDEFAULT_*_TO_SKILLS. Do not add lint warnings for features that are projected as skills — only warn for features that are truly dropped. - Start from
agentsmesh target scaffold <id>when building a built-in target. Do not hand-write the 10 skeleton files the scaffold produces. - Write failing tests first for every new behavior. Do not implement first and backfill later.
- Add unit, integration, and e2e coverage for the complete import and generate flow, including global scope when applicable.
- Add rich and realistic fixtures for the new target. Fixtures must resemble real projects, not toy placeholders.
- Cover all edge cases for the new target, including legacy paths, fallbacks, malformed files, partial support, and unsupported features.
- Wire descriptor capabilities for both project and global scope. New targets must include global mode unless the target has no global config surface at all, and that absence must be documented.
- Update every affected command surface and user-facing document so the new target is discoverable and accurately described.
- Update the compatibility matrix to reflect native, embedded, partial, or unsupported features. The matrix auto-builds from descriptor capabilities;
pnpm matrix:verifymust pass. The same script auto-generates the import-targets table, homepage tool list, and README tool list from descriptormetadata— no manual edits to those tables. - Update init detection and import empty-state messaging for the new target when native files exist.
- Reuse existing capability-focused tests where possible; extend them instead of duplicating assertions across multiple files.
- Preserve the canonical
.agentsmesh/contract. If the target cannot represent a feature natively, model that explicitly instead of inventing fake native output. - Ensure every internal file link or reference inside generated or imported Markdown artifacts is convertible through the shared reference-rewrite pipeline, just like the existing targets. Do not ship a new target unless canonical
.agentsmesh/references round-trip cleanly across that target's Markdown surfaces. - Run the full verification stack, including the packaging gates (
pnpm attw,pnpm publint,pnpm consumer-smoke), before claiming completion. - Run the
post-feature-qaskill before marking the task done.
What ships with it
1 file 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.
- 3d ago First seen · 103 lines · 62 tokens per session scan A 10f960dcc40b
add-agent-target is a skill published in the GitHub repository sampleXbro/agentsmesh (24 stars, last pushed 4d ago), licensed MIT. It adds 62 tokens to every session and 1,880 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 2026-08-30.
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