consult-zai
Orchestrates dual-AI analysis to provide comparative insights for complex coding queries.
Install
mkdir -p .claude/skills/consult-zai && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5317" && unzip -o skill.zip -d .claude/skills/consult-zai && rm skill.zipInstalls to .claude/skills/consult-zai
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Compare z.ai GLM 4.7 and code-searcher responses for comprehensive dual-AI code analysis. Use when you need multiple AI perspectives on code questions.Key capabilities
- →Executes parallel analysis with two distinct AI models
- →Generates line-referenced evidence for findings
- →Assigns confidence scores to code recommendations
- →Standardizes output structure for comparative analysis
- →Provides architecture and debugging perspectives
How it works
It triggers simultaneous prompts across two specialized model tools and aggregates the outputs into a unified, formatted report.
Inputs & outputs
When to use consult-zai
- →Deep code architectural review
- →Debugging hard to trace bugs
- →Comparative analysis of code implementation
- →High-value research for complex codebases
About this skill
Dual-AI Consultation: z.ai GLM 5.2 vs Code-Searcher
You orchestrate consultation between z.ai's GLM 5.2 model and Claude's code-searcher to provide comprehensive analysis with comparison.
When to Use This Skill
High value queries:
- Complex code analysis requiring multiple perspectives
- Debugging difficult issues
- Architecture/design questions
- Code review requests
- Finding specific implementations across a codebase
Lower value (single AI may suffice):
- Simple syntax questions
- Basic file lookups
- Straightforward documentation queries
Workflow
When the user asks a code question:
1. Build Enhanced Prompt
Problem-restate pre-flight (non-blocking). Before building the prompt, emit ONE line restating the code question you are about to dispatch (and, only if genuinely ambiguous, the alternative reading), then proceed:
Reading this as: «one-line restatement» (alt: «other reading», if any) — proceeding to consult; interrupt now to correct the framing.
Emit-and-proceed — do not ask-and-wait (the orchestrator can't reliably detect its own misframing). One line, and it guards the whole dispatch against a wrong-framing run.
Wrap the user's question with structured output requirements:
[USER_QUESTION]
=== Analysis Guidelines ===
**Structure your response with:**
1. **Summary:** 2-3 sentence overview
2. **Key Findings:** bullet points of discoveries
3. **Evidence:** file paths with line numbers (format: `file:line` or `file:start-end`)
4. **Confidence:** High/Medium/Low with reasoning
5. **Limitations:** what couldn't be determined
**Line Number Requirements:**
- ALWAYS include specific line numbers when referencing code
- Use format: `path/to/file.ext:42` or `path/to/file.ext:42-58`
- For multiple references: list each on a SEPARATE line with its own file path
(avoid comma-separated multi-citation like `file.ts:45, 67, 98`)
- Include brief code snippets for key findings
**Examples of good citations:**
- "The authentication check at `src/auth/validate.ts:127-134`"
- "Configuration loaded from `config/settings.json:15`"
- "Error handling in `lib/errors.ts:45`, `lib/errors.ts:67-72`, and `lib/errors.ts:98`"
**Citations Index (required):** end your response with a fenced block, one line per
Key Finding (repeat each block entry's `file:line` inline in the finding as usual):
```citations
<finding #> — path/to/file.ext:LINE[-END]
```
Severity / no-manufacture block — ORCHESTRATOR-GATED. Append the block below to both agents' prompts identically ONLY when the query is a defect hunt / code review (bug, security audit, "what's wrong with…", "review this"). OMIT it for explanatory / "how does X work" questions, where "found nothing" is not meaningful. The orchestrator — which knows the query type — makes this include/omit decision once, BEFORE writing the prompt files; do not leave it to each agent to self-classify. When included, append exactly these two bullets (the text only — no leading marker):
- Tag each finding with a **Severity** — Critical (wrong/broken on expected inputs) · Warning (fails on unusual but valid inputs) · Info (noteworthy, not actionable). Severity is *impact*, orthogonal to the Confidence field (*certainty*).
- **Finding nothing is a valid, valuable result.** If the code is correct, say so plainly with one verifying note — do NOT manufacture issues to look thorough.
2. Invoke Both Analyses in Parallel
Setup (run first). $CLAUDE_PROJECT_DIR is not always exported into the Bash tool
shell, so resolve it with a $PWD fallback and ensure the tmp dir exists. Substitute the
resolved literal path for $PROJECT_DIR, and a freshly generated RUN_ID
(seconds-resolution + 4-char nonce, e.g. run-2026-07-04-143052-a7f3), into every command
below. The RUN_ID in temp filenames prevents collisions between two concurrent
invocations sharing $PROJECT_DIR/tmp.
PROJECT_DIR="${CLAUDE_PROJECT_DIR:-$PWD}"
# Validate BEFORE creating tmp — `mkdir -p` would otherwise make the check pass even
# for a bad path (it creates the dir, then `[ -d ]` always succeeds).
[ -d "$PROJECT_DIR" ] || { echo "ERROR: PROJECT_DIR '$PROJECT_DIR' is not a directory" >&2; exit 1; }
mkdir -p "$PROJECT_DIR/tmp"
# Pre-flight (fail fast, not after a 20-min hang). jq is a HARD dependency — the §2a
# parse recipe needs it — so abort now rather than warn-and-continue into opaque failures.
command -v jq >/dev/null 2>&1 || { echo "ERROR: 'jq' not found — required for output parsing; aborting" >&2; exit 1; }
# zai is a soft dependency (a shell function wrapping the claude CLI against z.ai's
# endpoint, loaded from ~/.zshrc or ~/.bashrc — hence the interactive-shell probes).
# Capture WHICH interactive shell resolves it; the dispatch below substitutes
# $INTERACTIVE_SHELL so a .bashrc-only setup on macOS still works. If neither shell
# resolves zai, skip its dispatch and label the run degraded (see §2 dispatch + §4).
ZAI_AVAIL=1; INTERACTIVE_SHELL=zsh
if zsh -i -c 'type zai' >/dev/null 2>&1; then ZAI_AVAIL=0; INTERACTIVE_SHELL=zsh
elif bash -i -c 'type zai' >/dev/null 2>&1; then ZAI_AVAIL=0; INTERACTIVE_SHELL=bash
else echo "WARNING: 'zai' not found in zsh or bash interactive shells — z.ai will be skipped"
fi
echo "ZAI_AVAIL=$ZAI_AVAIL" # MUST echo: shell vars don't persist across Bash tool calls
echo "INTERACTIVE_SHELL=$INTERACTIVE_SHELL" # substitute into the Step-2 dispatch below
# Sweep stale orphans (>60 min) from crashed prior runs (best-effort, age-based —
# can theoretically delete a live run's files if it paused >60 min; acceptable).
find "$PROJECT_DIR/tmp" -maxdepth 1 -name 'zai-prompt-*.txt' -mmin +60 -delete 2>/dev/null
find "$PROJECT_DIR/tmp" -maxdepth 1 -name 'zai-output-*.json' -mmin +60 -delete 2>/dev/null
find "$PROJECT_DIR/tmp" -maxdepth 1 -name 'zai-stderr-*.log' -mmin +60 -delete 2>/dev/null
# Resolve the timeout binary used to wrap the Step-2 z.ai dispatch so a hung CLI is
# bounded rather than running unbounded — the harness may auto-background the dispatch,
# letting it escape the Bash tool's own timeout. Homebrew coreutils installs GNU
# timeout as `gtimeout`; plain `timeout` exists only when the gnubin PATH is on. If
# neither exists, TIMEOUT_CMD stays empty → dispatch UNWRAPPED (best-effort;
# `brew install coreutils` restores the hard guard).
TIMEOUT_CMD=""
if command -v timeout >/dev/null 2>&1; then TIMEOUT_CMD="timeout"
elif command -v gtimeout >/dev/null 2>&1; then TIMEOUT_CMD="gtimeout"
fi
echo "TIMEOUT_CMD=$TIMEOUT_CMD" # substitute into the Step-2 dispatch (when empty: omit the wrap)
Two-phase dispatch (required). Tool calls in one message run concurrently, so emitting
the z.ai prompt-file Write and the z.ai dispatch together races the dispatch ahead of the
file existing (the cat pipes an empty/missing file). Use two messages: message 1
writes the z.ai prompt file (Step 1 below); message 2 issues the z.ai dispatch (Step 2)
and the Code-Searcher Agent call in parallel.
Gen-dispatch timeout watchdog (GEN_TIMEOUT=1200). The z.ai dispatch is wrapped in
$TIMEOUT_CMD -k 10 1200 (resolved in Setup) — SIGTERM at 1200s (20 min), SIGKILL 10s
later (-k 10, reaps orphaned Node/MCP children). This bounds a hung z.ai CLI that could
otherwise run unbounded (the harness may auto-background the dispatch, so the Bash tool's
own timeout is not a reliable cap). When TIMEOUT_CMD is empty: omit the
$TIMEOUT_CMD -k 10 1200 prefix and dispatch unwrapped — set the Bash tool's own
timeout parameter to 1300000 ms as a best-effort cap, and brew install coreutils to
restore the hard guard. On a timed-out dispatch (exit 124 = SIGTERM, 137 =
SIGKILL): the output file is empty/truncated, so the §2a [ -z … ] parse guard drops the
agent — treat z.ai as failed per §4 (present Code-Searcher's response and note the
timeout; do NOT retry). Code-Searcher (Agent tool) is not wrapped — it bounds itself.
-
For z.ai GLM 5.2:
Step 1: Write the enhanced prompt to a temp file using the Write tool:
Write to $PROJECT_DIR/tmp/zai-prompt-RUN_ID.txt with the ENHANCED_PROMPT contentStep 2: Execute z.ai (skip if Setup echoed
ZAI_AVAIL=1— no workingzai; present only the Code-Searcher response and label the report a degraded single-AI run: no cross-comparison, and note a direct Read or lighter path would have been cheaper). Pipe the prompt via stdin and capture output/stderr to files ($INTERACTIVE_SHELL= thezsh|bashliteral resolved in Setup):cat "$PROJECT_DIR/tmp/zai-prompt-RUN_ID.txt" | \ $TIMEOUT_CMD -k 10 1200 $INTERACTIVE_SHELL -i -c "zai --bare --print --output-format json --model 'glm-5.2[1m]' --allowedTools 'Read,Grep,Glob' --disallowedTools 'Bash,Edit,Write,NotebookEdit,WebFetch,WebSearch,Task,KillShell,BashOutput' --add-dir '$PROJECT_DIR'" \ > "$PROJECT_DIR/tmp/zai-output-RUN_ID.json" \ 2> "$PROJECT_DIR/tmp/zai-stderr-RUN_ID.log"Why this exact form (each piece prevents a failure seen in practice):
--bareis required —zaiexportsANTHROPIC_AUTH_TOKEN; without--barethe parent session's OAuth token shadows it → 401 against the z.ai endpoint.--model 'glm-5.2[1m]'is required — guarantees GLM 5.2 regardless of which tier default resolution would pick (guards against theglm-5-turbosubagent default).- Read-only enforcement =
--allowedTools 'Read,Grep,Glob'plus the load-bearing--disallowedTools 'Bash,Edit,Write,NotebookEdit,WebFetch,WebSearch,Task,KillShell,BashOutput'—--allowedToolsonly auto-approves and does NOT deny unlisted tools, so a global~/.claude/settings.jsonallow-list would otherwise re-permit write-capable Bash on the--barepath (verified 2026-07-18); consultation is analysis, never modification. Freeze the reviewed tree while agents run: you, the orchestrator, must not edit, `git ch
Content truncated.
When not to use it
- →Simple file lookups
- →Basic syntax error questions
- →Single-line documentation queries
Limitations
- →Increased token usage due to dual model invocation
- →Requires consistent context to keep models aligned on the same codebase
How it compares
It forces dual-model perspectives to mitigate individual AI hallucinations or narrow reasoning.
Compared to similar skills
consult-zai side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| consult-zai (this skill) | 1 | 6mo | Review | Intermediate |
| codex | 32 | 2mo | Review | Advanced |
| jupyter-notebook | 30 | 6mo | Review | Intermediate |
| senior-fullstack | 35 | 7mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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