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/melodic-software/claude-code-plugins/targetnpx skills add melodic-software/claude-code-plugins --skill targetgit clone --depth 1 https://github.com/melodic-software/claude-code-pluginsWrote 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/melodic-software/claude-code-plugins/target)<a href="https://agentmods.dev/skills/melodic-software/claude-code-plugins/target"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/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 5.1 | $0.00204 | $0.01549 |
| Opus 5 | $0.00102 | $0.00775 |
| Sonnet 5 | $0.00041 | $0.00310 |
| Haiku 4.5 | $0.00020 | $0.00155 |
Grade A, and why
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 2d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Answers "what should we optimize, and how much do we actually know about it?"
The failure this prevents is picking a target because its mechanism sounds expensive. In the source run behind this plugin, a parallel session diagnosed WDAC code-integrity enforcement as the cause of slow process spawns. The mechanism was real and the policy was genuinely enabled. It was still the wrong answer, and had to be retracted: a spread of min 180.5 ms / median 1107.7 ms / max 2841.3 ms across identical no-op spawns is a contention signature, because a fixed policy check cannot produce a 15x spread. The bimodality was the diagnosis; the plausible mechanism was a distraction.
So this skill ranks by evidence, and says so when there is none.
Inputs it accepts
| Source | What to do |
|---|---|
| The current session's own pain | Name the operation that felt slow and what was observed. Anecdote is a valid candidate source and an invalid ranking basis. |
| A named path or component | Enumerate the layers it spans before choosing one (see "Measure the layers first"). |
| A telemetry store | /claude-ops:observability for Claude Code's own; otherwise the project's. Prefer it over every other source. |
| Open-ended "what is slow here" | Widest scope, weakest evidence. Expect the output to be "instrument this first". |
Evidence tiers
Rank every candidate into exactly one. A lower tier never outranks a higher one, regardless of how compelling the mechanism sounds.
| Tier | Means | Example |
|---|---|---|
| E1, attributed measurement | A measurement that isolates this component's cost from its neighbours' | A spawn census showing this hook costs 4 of the 7 spawns per tool call |
| E2, aggregate measurement | A real measurement that includes this component but does not isolate it | "The whole pre-tool path takes 1.2 s" |
| E3, structural inference | No measurement; a documented cost model predicts expense | "This is a 125-line shell wrapper that runs per tool call" |
| E4, suspicion | A plausible mechanism and nothing else | "WDAC is probably slowing spawns" |
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.
- 2d ago First seen · 111 lines · 204 tokens per session scan A 55de9ff7f228
target is a skill published in the GitHub repository melodic-software/claude-code-plugins (15 stars, last pushed today), licensed MIT. It adds 204 tokens to every session and 1,549 once invoked, about $0.0010 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 2026-09-03.
Other skills, from other repositories
parallel-orchestrator
Manage parallel Claude Code workstreams using git worktrees. Use when: splitting large tasks across multiple workers, coordinating parallel development, monitoring worker progress, integrating completed work, analyzing work item documents (code reviews, issue lists). Triggers: parallel, orchestrator, worktrees…
parallel-worker
Execute focused implementation tasks in a parallel workflow. Use when: working on assigned files in a worktree, making checkpoint commits, signaling dependencies or blockers, completing orchestrator-assigned tasks. Triggers: worker, checkpoint, worktree, assigned scope, commit prefix, parallel task.
solve-constraint-puzzle
For constraint satisfaction: Sudoku, scheduling, N-queens, logic puzzles, SAT-like problems, assignment problems. Uses propagate-then-search pattern.
use-class-for-state
For complex state: encapsulate multiple interacting variables, stateful algorithms, backtracking search state.
build-priority-queue
For ordered processing: A search, Dijkstra, event simulation, task scheduling. Efficient min/max extraction with heap-based queue.
catch-expected-errors
For iteration with errors: catch exceptions during exploration, skip invalid cases, continue to next attempt.