Borrowing it
Nothing to install: this file belongs to fruggr/zendesk-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fruggr/zendesk-mcp-server/main/.claude/skills/probe-spike/SKILL.mdgit clone --depth 1 https://github.com/fruggr/zendesk-mcp-serverWrote 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/fruggr/zendesk-mcp-server/probe-spike)<a href="https://agentmods.dev/skills/fruggr/zendesk-mcp-server/probe-spike"><img src="https://agentmods.dev/badge/skills/fruggr/zendesk-mcp-server/probe-spike/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/fruggr/zendesk-mcp-server/probe-spike"><img src="https://agentmods.dev/badge/skills/fruggr/zendesk-mcp-server/probe-spike.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 | $0.00077 | $0.01036 |
| Opus 5.5 | $0.00031 | $0.00414 |
| Sonnet 5.5 | $0.00015 | $0.00207 |
| Haiku 4.5 | $0.00008 | $0.00104 |
Grade A, and why
probe-spike scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Hard rules first**: never read, print, export or `curl` with the token How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Probe spike — scope from ground truth, then plan
Zendesk's docs are thin on response shapes, and the tools return formatted text, never raw JSON. A plan built on a guessed shape fails late: types, mocks and tests all encode the guess. So when a plan rests on such a fact, measure it on a live tenant before writing the plan. Order: spike → report → plan → owner's go → code. No feature code before the plan is approved.
Skip the spike when every fact the plan needs is already observable through the MCP tools, or already pinned by a mock that a live run confirmed.
Author side
- List the questions. Each one is a fact the plan branches on (Q1, Q2…),
stated so a yes/no or a shape answers it. Mark which can be answered through
the existing
mcp__<server>__*tools and which need raw payloads. - Write the probe for the raw-payload questions:
scripts/probe-<topic>.ts, following the conventions indocs/live-testing.md(Probes). In particular:- credentials from
scripts/live-auth.ts, never from the caller; - GETs only, through
zendeskGet(rawfetchonly for a header question); - print keys, ids, stages, timestamps, numbers — never subjects, bodies or names;
- a failing step is a finding: report it and carry on;
- auto-discover a sample that can actually answer the question (a ticket
that carries an SLA, a non-empty view) instead of trusting a hard-coded id.
Gates:
pnpm typecheck,pnpm check. A probe is dev tooling, exempt from a functional validation plan.
- credentials from
- Open a draft PR carrying the probe and a
## Spike protocolsection in its description, written for an agent that has none of your context:- Hard rules first: never read, print, export or
curlwith the token (the session security classifier blocks it; every step resolves the credential itself); read-only in Zendesk; no subjects, bodies or names in the report. - Environment: assume a ready one, as in
functional-validation-plan(on the branch,zendesk-localrunning and signed in). Do not make the executor install, build or configure anything. - Steps: the probe command(s), then the MCP tool calls that give today's
baseline, then any client facts needed (
claude --version, OS). - Human hand-offs: say exactly what to ask the human when the tenant lacks the state a question needs (a view column, an SLA policy). The executor asks; it never changes the tenant itself.
- Report shape: one section per question, then anomalies, then the raw
probe output in a collapsed
<details>block.
- Hard rules first: never read, print, export or
- Subscribe to the PR and wait for the report. Do not start coding.
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.
- 4d ago First seen · 74 lines · 77 tokens per session scan A b66188a05dee
probe-spike is a skill published in the GitHub repository fruggr/zendesk-mcp-server (14 stars, last pushed today), licensed MIT. It adds 77 tokens to every session and 1,036 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-21.
Other skills, from other repositories
opik-diagnose
Surface the Opik traces worth a developer's attention, ranked by signal — Diagnostics issues first, then errors, failed tool calls, latency, regressions, and low online-eval scores. With the Opik MCP connected it lists the project's agentinsightsissue entities, offers to turn Diagnostics on when the project has it…
cortex-explore-memory
Explore the memory system's state, find gaps in knowledge, assess coverage, and get diagnostic information. Use when the user asks 'what does my memory look like', 'show me memory stats', 'what am I missing', 'how good is my knowledge', 'memory health', 'show coverage', 'find gaps', 'what topics are weak', or when you…
qmclaw-workbench
A local simulator for superconducting quantum-bit experiments, including measurements used to study and tune a qubit. It produces bounded synthetic results without connecting to laboratory hardware or quantum cloud services.
quantum-fermi-hubbard-vqe
A variational quantum simulation of the open-boundary Fermi–Hubbard chain, a model of particles hopping between sites and interacting when they occupy the same system. It maps the model to qubits with the Jordan–Wigner transformation and searches for a low-energy state.
quantum-grover
A Qiskit implementation of Grover's algorithm, a quantum search method that increases the chance of finding a marked item. It can explain the method, build an explicit quantum circuit, or run it with chosen inputs.
guppy-programs
A compiler and simulator for structured quantum programs with measurements, qubit reset, and gates chosen by earlier measurement results. It uses Guppy and Selene to model these dynamic circuits locally.