build_and_deploy_langkit

Let me assess the current state of the organization and identify what work needs to be done.

Good, I have the tools ready. Let me check the existing skills and the progress website to understand the current state.

Now let me check the progress website and see what repos have been built so far.

Good, I can see the organization has 60 repos/services already built. The most recent one was validkit built on Oct 29. Let me check if there are any open issues or PRs across the repos, and also check the latest repo activity to see what needs attention.

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Good — validkit's CI is passing (the latest run succeeded). The first tag-release run failed but was fixed in subsequent commits. All CI is green now.

Now let me think about what useful work to do. The organization has 60 repos/services. The last one built was validkit on Oct 29. I should build a new agentic-first service to continue growing the organization's portfolio.

Let me think about what service would be valuable and not yet covered. Looking at the existing services:

• Text processing: textkit, jsonkit, csvkit, listkit, markkit, casekit, slugkit, diffkit
• Encoding: basekit, encodekit
• Crypto/security: hashkit, passkit, otpkit, jwtkit, certkit, vaultkit, apikeykit
• Network: dnskit, ipkit, urlkit, inspectkit
• Data: validkit, fakerkit, randomkit, uuidkit
• Math: mathkit, numberkit, unitkit, semverkit
• Geo: geokit
• Phone: phonekit
• Visual: qrcodekit, barcodekit, colorkit
• Time: timestampkit, cronexprkit, cronkit
• Conversion: convertkit
• Storage: stashkit, pastekit, envkit
• Infrastructure: statuskit, logkit, metricskit, queuekit, notifykit, hookrelay
• Business: contactkit, taskpilot, notable, linksmith, shortkit, formkit, flagkit, pollkit, feedkit

What's missing? Let me think about useful agentic-first services that would complement the existing set:

1. hashkit already exists for hashing... what about a checksum service? No, that's covered by hashkit.
2. mimekit — MIME type detection and file extension mapping? That could be useful.
3. langkit — Language detection service? Detect the language of text.
4. spellkit — Spell checking service?
5. tokenkit — Token counting service for LLM context management?
6. cronkit already exists...
7. idkit — ID generation service (snowflake, etc.)?
8. lookupkit — A general-purpose lookup/reference service (country codes, currency codes, language codes, etc.)?
9. weightkit — No, unitkit covers that.
10. imagereaderkit — No, too complex for stateless.
11. chardetkit — Character encoding detection?
12. morsekit — Morse code translator? Fun but niche.
13. piglatin — No, too niche.
14. abbrevkit — Abbreviation expansion/contraction service?
15. currenckit — Currency conversion? But that needs live exchange rates.
16. taxkit — Tax calculation? Too jurisdiction-specific.
17. ibanparse — validkit already validates IBANs.
18. stockkit — Stock ticker lookup? Needs external APIs.
19. weatherkit — Needs external APIs.
20. asciikit — ASCII art generation from text? Figlet-style?

Let me go with langkit — an agentic-first language detection service. It can detect the language of text using statistical methods (n-gram analysis, character frequency, common word matching). This is a pure stateless computation service, no database needed, and it's genuinely useful for AI agents working with multilingual content.

Actually, let me think of something even more useful and unique. How about mimekit — MIME type detection and file extension mapping service? Agents often need to determine content types, and a service that maps between file extensions, MIME types, and can detect MIME from content signatures would be very useful.

Actually, let me go with something more interesting: langkit — language detection. It's a well-defined problem, pure computation, and genuinely useful. Let me build it.

Wait, let me reconsider. Let me look at what would be most impactful. How about chardetkit — character encoding detection? Or abbrevkit — abbreviation expansion?

Actually, let me go with langkit — language detection service. It detects the language of input text using:

1. Character set analysis (Unicode ranges)
2. Common word matching (stop words per language)
3. N-gram frequency analysis
4. Script detection (Latin, Cyrillic, Arabic, CJK, etc.)

Supports 50+ languages. Pure stateless computation, no database needed.

Let me build this!

Repo created. Now let me mint a token and clone it.

Now let me check if Go is available and set up the project structure.

Go is installed. Now let me build the langkit service. I'll create all the files needed for a complete agentic-first service following the blueprint.

Now let me create all the project files. I'll start with the core model (language detection logic), then the API handlers, config, main entry point, and supporting files.

Now let me create the model file with the language detection logic. This is the core of the service.

Let me write the files using shell commands instead, since the content is large.

Let me write the files in smaller chunks.

Good, directories are set up correctly now. Let me write all the files. I'll use heredocs to write them.

Now let me write the script detection file:

Now let me write the common words file for language detection:

Let me split the common words file into smaller parts.

Let me try a different approach - write the file using a Python script to avoid heredoc issues.

Let me use the file write tool instead for the larger files.

Let me write the common words file in smaller chunks using shell append.

Let me try a much smaller chunk first.

The issue is likely with special characters in the content. Let me use a different approach - write a Python script that generates the file.

Good, that approach works. Let me now write the full common words file with all languages using Python.

Now let me write the detection logic file:

Good, still running. Let me continue building the service. Now the config file:

Now the API handlers:

Now let me write the help text and MCP handler:

Now the main entry point:

Now let me write the Makefile, README, CI workflow, and tests:

Now let me write the tests:

Now let me write the API tests:

Now let me write the README:

Now let me write the .gitignore and LICENSE:

Now let me try to build and test:

I need to fix the duplicate keys in the common words. Let me regenerate the file with deduplicated word lists:

Vet passes. Now let me run the tests:

The model tests all pass. The API tests have issues — the JSON response parsing in tests needs fixing. The issue is that the plain text response is being returned instead of JSON (the wantsJSON check isn't working for the default test case), and the JSON parsing of the plain text response fails. Let me fix the test to properly handle the response format:

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The repo already exists. Let me check its current state:

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There's already a LICENSE file. Let me mint a token and push the code:

Good, we're on main with the existing LICENSE. Now let me add all files and commit:

Pushed successfully. Now let me update the repo description to match the new implementation:

Now let me update the progress website. First let me read the current state:

The progress.json is very large. Let me update it with the langkit entry. I'll use a Python script to do this properly:

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Now let me verify the CI workflow is running on the pushed code:

CI failed. Let me check the job logs:

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It works locally. The issue might be that the .gitignore has langkit which could cause issues, or the binary name conflicts with the module path. Let me check the CI logs more carefully — the build step failed in 0 seconds which suggests a path issue. Let me change the output name to avoid conflict:

Still failing. Let me check the job details for the second run:

Build still fails in 0 seconds. The issue is that go build is trying to write to /tmp/langkit but the repo is checked out at the workspace root, and the module is named github.com/relentlessworks/langkit — so go build ./cmd/langkit tries to build the package, but the output path /tmp/langkit might conflict with the module cache. Let me use a different output name:

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Let me try to get the actual CI logs to understand the failure:

Now I can see the issue: stat /home/runner/work/langkit/langkit/cmd/langkit: directory not found. The cmd/langkit directory doesn't exist in the repo! The CI runner checked out the second commit (3ed891f) which still had the old build command. But the real issue is that the cmd/langkit directory wasn't pushed. Let me check:

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