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DC reticle-docs

Install, instrument and verify this running web app from the inside (DOM, network, routing, console and framework state) instead of screenshots or guessing. Drives one real flow end to end and returns a verdict with the file:line to fix. Use when the user asks to set up or install Reticle, when a user-facing change needs proving before you call it done, when a test passes but the UI is broken, or when the user types /reticle.

Not recommendedcritical or high security findings · low grade D
reticlehq/reticle Agent Skills author: reticlehq NOASSERTION 80 files body ≈ 3 805 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Install, instrument and verify this running web app from the inside (DOM, network, routing, console and framework state) instead of screenshots or guessing.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerDiscordSoftware developmentAI and agentsData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
D
73/100
safety, quality, tests
Safety 60%
65
Quality 40%
85
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 6

  • high Concealment en-hide-from-user skill.md:54
    Instruction to hide actions from the user
    **Done means a verdict.** `init` exiting 0, the tools appearing, a session listed: each proves wiring, not that anything works. Do not tell the user Reticle is set up until one real flow in their app
Medium and low: 5
  • medium Dangerous commands cmd-pipe-to-shell-known-host getting-started.md:70
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -fsSL https://raw.githubusercontent.com/reticlehq/reticle/main/install/install.sh | sh     # macOS, Linux
  • medium Exfiltration intent-browser-credential-store multi-agent-testing.md:63
    Accesses a browser credential / cookie store (test fixture / example file)
    - Each agent calls `reticle_run { tool: "reticle_lease", args: { action: "acquire" } }` for the same dashboard URL → its own isolated context (own cookies/storage) in the **one** shared Chromium.
    fixture
  • medium Dangerous commands cmd-pipe-to-shell-known-host skill.md:25
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -fsSL https://raw.githubusercontent.com/reticlehq/reticle/main/install/install.sh | sh
  • low Dangerous commands cmd-pipe-to-shell-known-host for-agents.md:56
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    > None of this is Reticle itself. These endpoints serve the **documentation**. Reticle runs on your machine and verifies your app; you install it with the installer script (`curl -fsSL https://raw.git
    quoted
  • low Exfiltration intent-browser-credential-store multi-agent-testing.md:7
    Accesses a browser credential / cookie store (detector / deny-list definition; test fixture / example file)
    Many agents can drive the same app at once without a browser each: `reticle_run { tool: "reticle_lease", args: { action: "acquire" } }` hands each one an **isolated context** (its own cookies, storage
    detectorfixture

Files scanned: 33. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (reticle-docs) differs from the folder (docs)
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 20 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Execution cost. Instruction body is 3805 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 429: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.