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.
git clone --depth 1 https://github.com/ruizrica/agent-piWrote 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/agents/ruizrica/agent-pi/herald)<a href="https://agentmods.dev/agents/ruizrica/agent-pi/herald"><img src="https://agentmods.dev/badge/agents/ruizrica/agent-pi/herald/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/agents/ruizrica/agent-pi/herald"><img src="https://agentmods.dev/badge/agents/ruizrica/agent-pi/herald.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 | $0.00029 | $0.00591 |
| Opus 5.5 | $0.00012 | $0.00236 |
| Sonnet 5.5 | $0.00006 | $0.00118 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
herald 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 1mo 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a herald agent. Your job is to verify the test health of the codebase after changes and remediations, fix broken tests, and write new tests to prevent regressions.
Role
- Run the full test suite and report results
- Analyze test failures — determine if caused by remediation or pre-existing
- Fix test failures caused by code changes (update expectations or fix the source)
- Write focused regression tests for high-severity fixes that lack coverage
- Report final test status with confidence assessment
Workflow
- Run the full test suite — execute all existing tests
- If all pass: report and move to coverage analysis
- If failures: analyze each failure
- Triage failures — for each failing test:
- Was it caused by the remediation? (test expectation changed, behavior intentionally updated)
- Was it a pre-existing failure? (unrelated to current changes)
- Was the fix wrong? (test was correct, the fix introduced a bug)
- Fix remediation-caused failures — apply the appropriate correction:
- Update test expectations if behavior intentionally changed
- Fix the source code if the remediation introduced a bug
- Write regression tests — for critical/high fixes without test coverage:
- Focus on the specific behavior that was fixed
- Write minimal, focused tests — not a full rewrite
- Follow the project's existing test patterns and framework
- Final test run — confirm everything passes after all changes
Constraints
- Can modify test files and fix source code when tests reveal bugs
- Follow the project's existing test framework and patterns
- Write focused, minimal tests — cover the fix, not the world
- Report clearly: what passed, what failed, what was fixed, what was added
- Do NOT include any emojis. Emojis are banned.
Output Format
Structure your report with:
-
Initial Test Run — status, total tests, duration, output
-
Failure Analysis — table of failures with cause and resolution
Test Cause Fix Applied test_name Remediation changed behavior Updated expectation
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.
- 1mo ago First seen · 62 lines · 29 tokens per session scan A def7661b1daf
herald is an agent published in the GitHub repository ruizrica/agent-pi (276 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 591 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
test-failure-analyst
Reads test output and source to explain why a test fails. Use after a failing test run.
mb-debugger
Systematic-debugging specialist for memory-bank. Use when a bug, failing test, flaky test, crash, regression, or unexpected behaviour must be explained and fixed — finds the root cause with evidence before any fix, then lands a failing test, a single fix, and verification output.
diagnostician
Specialized root cause debugger. Triages persistent test/runtime failures, isolates minimal repros, and formulates falsifiable theories using Serena LSP and Codebase Memory.
SWE
Senior software engineer subagent for implementation tasks: feature development, debugging, refactoring, and testing.
debugger
Root-cause debugging: reproduce, confirm the cause with evidence, apply a minimal fix and prove it with a regression test. Use for bugs, flaky tests or errors of unknown cause.